Large Language Model Based Long Context Modeling Papers and Blogs

This repository includes papers and blogs about Efficient Transformers, KV Cache, Length Extrapolation, Long-Term Memory, Retrieval-Augmented Generation (RAG), Compress, Long Text Generation, Long Video, Long CoT and Evaluation for Long Context Modeling.

🔥 Must-read papers for LLM-based Long Context Modeling.

🔥⚡🔥 Thanks for all the great contributors on GitHub!

🚀🤝🚀 I have the privilege of joining [LCLM-Horizon] and collaborating with them on providing a very complete and comprehensive scholarly survey (A Comprehensive Survey on Long Context Language Modeling) and repository (A-Comprehensive-Survey-For-Long-Context-Language-Modeling) dedicated to Long Context Language Modeling. I look forward to collaborating with them to advance research and deepen understanding in this area!

If you find our repository and survey useful for your research, please consider citing the following paper:

@article{liu2025comprehensive,
  title={A Comprehensive Survey on Long Context Language Modeling},
  author={Liu, Jiaheng and Zhu, Dawei and Bai, Zhiqi and He, Yancheng and Liao, Huanxuan and Que, Haoran and Wang, Zekun and Zhang, Chenchen and Zhang, Ge and Zhang, Jiebin and others},
  journal={arXiv preprint arXiv:2503.17407},
  year={2025}
}

Contents

• Large Language Model Based Long Context Modeling Papers and Blogs
  • Contents
  • 📢 News
    • Week Papers
    • Month Papers
  • 📜 Papers
    • 1. Survey Papers
    • 2. Efficient Attention
      • 2.1 Sparse Attention
      • 2.2 Linear Attention
      • 2.3 Hierarchical Attention
      • 2.4 IO-Aware Attention
    • 3. Recurrent Transformers
    • 4. State Space Models
    • 5. Long-Context LLMs
      • 5.1 Length Extrapolation
      • 5.2 Test-Time Training
    • 6. Long Term Memory
    • 7. RAG and ICL
    • 8. Agent
    • 9. Compress
      • 9.1 Context
      • 9.2 Model
      • 9.3 Long CoT
      • 9.4 Latent
    • 10. Long Video and Image
      • 10.1 Offline
      • 10.2 Streaming
      • 10.3 Frame Selection
      • 10.4 Vision Language Action
    • 11. Benchmark and Evaluation
      • 11.1 LLM
      • 11.2 MLLM
      • 11.3 Agentic
    • 12. Long Text Generation
    • 13. Long CoT
      • 13.1 LLM
      • 13.2 MLLM
    • 14. Speculative Decoding
    • 15. Technical Report
    • 16. Blogs
  • Acknowledgements
    • Contributors
    • Star History

📢 News

Week Papers

• [2026.02.27]

  • Paper: OneVision-Encoder: Codec-Aligned Sparsity as a Foundational Principle for Multimodal Intelligence
  • Paper: XStreamVGGT: Extremely Memory-Efficient Streaming Vision Geometry Grounded Transformer with KV Cache Compression

• [2026.01.27]

  • Paper: Elastic Attention: Test-time Adaptive Sparsity Ratios for Efficient Transformers
  • Paper: Soft Tail-dropping for Adaptive Visual Tokenization
  • Paper: HERMES: KV Cache as Hierarchical Memory for Efficient Streaming Video Understanding
  • Paper: BFA++: Hierarchical Best-Feature-Aware Token Prune for Multi-View Vision Language Action Model
  • Paper: LongVideo-R1: Smart Navigation for Low-cost Long Video Understanding

• [2026.01.26]

  • Paper: HIPPO: Accelerating Video Large Language Models Inference via Holistic-aware Parallel Speculative Decoding

• [2026.01.22]

  • Paper: Extending the Context of Pretrained LLMs by Dropping Their Positional Embeddings
  • Paper: RePo: Language Models with Context Re-Positioning
  • Paper: Fast-weight Product Key Memory
  • Paper: HERMES: KV Cache as Hierarchical Memory for Efficient Streaming Video Understanding

• [2026.01.21]

  • Paper: Chain-of-Thought Compression Should Not Be Blind: V-Skip for Efficient Multimodal Reasoning via Dual-Path Anchoring
  • Paper: Hierarchical Long Video Understanding with Audiovisual Entity Cohesion and Agentic Search
  • Paper: Beyond Accuracy: Evaluating Grounded Visual Evidence in Thinking with Images
  • Paper: Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning
  • Paper: AgentOCR: Reimagining Agent History via Optical Self-Compression

• [2026.01.19]

  • Paper: Think-Clip-Sample: Slow-Fast Frame Selection for Video Understanding
  • Paper: Explore with Long-term Memory: A Benchmark and Multimodal LLM-based Reinforcement Learning Framework for Embodied Exploration

• [2026.01.16]

  • Paper: Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding

• [2026.01.15]

  • Paper: See More, Store Less: Memory-Efficient Resolution for Video Moment Retrieval
  • Paper: STEP3-VL-10B Technical Report

• [2026.01.13]

  • Paper: Watching, Reasoning, and Searching: A Video Deep Research Benchmark on Open Web for Agentic Video Reasoning
  • Paper: Speak While Watching: Unleashing TRUE Real-Time Video Understanding Capability of Multimodal Large Language Models
  • Paper: MHLA: Restoring Expressivity of Linear Attention via Token-Level Multi-Head
  • Paper: Let's (not) just put things in Context: Test-Time Training for Long-Context LLMs

• [2026.01.12]

  • Paper: MMViR: A Multi-Modal and Multi-Granularity Representation for Long-range Video Understanding
  • Paper: VideoAuto-R1: Video Auto Reasoning via Thinking Once, Answering Twice

• [2025.12.17]

  • Paper: Zoom-Zero: Reinforced Coarse-to-Fine Video Understanding via Temporal Zoom-in
  • Paper: TimeLens: Rethinking Video Temporal Grounding with Multimodal LLMs
  • Paper: SAGE: Training Smart Any-Horizon Agents for Long Video Reasoning with Reinforcement Learning

• [2025.12.04]

  • Paper: AdaptVision: Efficient Vision-Language Models via Adaptive Visual Acquisition
  • Paper: UniComp: Rethinking Video Compression Through Informational Uniqueness
  • Paper: EEA: Exploration-Exploitation Agent for Long Video Understanding
  • Paper: Divide, then Ground: Adapting Frame Selection to Query Types for Long-Form Video Understanding

Month Papers

📜 Papers

You can directly click on the title to jump to the corresponding PDF link location

1. Survey Papers

1. Efficient Transformers: A Survey. Yi Tay, Mostafa Dehghani, Dara Bahri, Donald Metzler. Arxiv 2022.

2. A Survey on Long Text Modeling with Transformers. Zican Dong, Tianyi Tang, Lunyi Li, Wayne Xin Zhao. Arxiv 2023.

3. Neural Natural Language Processing for Long Texts: A Survey of the State-of-the-Art. Dimitrios Tsirmpas, Ioannis Gkionis, Ioannis Mademlis, Georgios Papadopoulos. Arxiv 2023.

4. Advancing Transformer Architecture in Long-Context Large Language Models: A Comprehensive Survey. Yunpeng Huang, Jingwei Xu, Zixu Jiang, Junyu Lai, Zenan Li, Yuan Yao, Taolue Chen, Lijuan Yang, Zhou Xin, Xiaoxing Ma. Arxiv 2023.

5. Length Extrapolation of Transformers: A Survey from the Perspective of Position Encoding. Liang Zhao, Xiaocheng Feng, Xiachong Feng, Bing Qin, Ting Liu. Arxiv 2024.

6. The What, Why, and How of Context Length Extension Techniques in Large Language Models -- A Detailed Survey. Saurav Pawar, S.M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain, Aman Chadha, Amitava Das. Arxiv 2024.

7. State Space Model for New-Generation Network Alternative to Transformers: A Survey. Xiao Wang, Shiao Wang, Yuhe Ding, Yuehang Li, Wentao Wu, Yao Rong, Weizhe Kong, Ju Huang, Shihao Li, Haoxiang Yang, Ziwen Wang, Bo Jiang, Chenglong Li, Yaowei Wang, Yonghong Tian, Jin Tang. Arxiv 2024.

8. A Survey on Efficient Inference for Large Language Models. Zixuan Zhou, Xuefei Ning, Ke Hong, Tianyu Fu, Jiaming Xu, Shiyao Li, Yuming Lou, Luning Wang, Zhihang Yuan, Xiuhong Li, Shengen Yan, Guohao Dai, Xiao-Ping Zhang, Yuhan Dong, Yu Wang. Arxiv 2024.

9. A Survey on RAG Meets LLMs: Towards Retrieval-Augmented Large Language Models. Yujuan Ding, Wenqi Fan, Liangbo Ning, Shijie Wang, Hengyun Li, Dawei Yin, Tat-Seng Chua, Qing Li. Arxiv 2024.

10. Evaluation of Retrieval-Augmented Generation: A Survey. Hao Yu, Aoran Gan, Kai Zhang, Shiwei Tong, Qi Liu, Zhaofeng Liu. Arxiv 2024.

11. The CAP Principle for LLM Serving: A Survey of Long-Context Large Language Model Serving. Pai Zeng, Zhenyu Ning, Jieru Zhao, Weihao Cui, Mengwei Xu, Liwei Guo, Xusheng Chen, Yizhou Shan. Arxiv 2024.

12. Keep the Cost Down: A Review on Methods to Optimize LLM' s KV-Cache Consumption. Luohe Shi, Hongyi Zhang, Yao Yao, Zuchao Li, Hai Zhao. Arxiv 2024.

13. Contextual Compression in Retrieval-Augmented Generation for Large Language Models: A Survey. Sourav Verma. Arxiv 2024.

14. Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely. Siyun Zhao, Yuqing Yang, Zilong Wang, Zhiyuan He, Luna K. Qiu, Lili Qiu. Arxiv 2024.

15. Prompt Compression for Large Language Models: A Survey. Zongqian Li, Yinhong Liu, Yixuan Su, Nigel Collier. Arxiv 2024.

16. A Survey of RWKV. Zhiyuan Li, Tingyu Xia, Yi Chang, Yuan Wu. Arxiv 2024.

17. A Survey on Large Language Model Acceleration based on KV Cache Management. Haoyang Li, Yiming Li, Anxin Tian, Tianhao Tang, Zhanchao Xu, Xuejia Chen, Nicole Hu, Wei Dong, Qing Li, Lei Chen. Arxiv 2024.

18. A Survey on Mamba Architecture for Vision Applications. Fady Ibrahim, Guangjun Liu, Guanghui Wang. Arxiv 2025.

19. Thus Spake Long-Context Large Language Model. Xiaoran Liu, Ruixiao Li, Mianqiu Huang, Zhigeng Liu, Yuerong Song, Qipeng Guo, Siyang He, Qiqi Wang, Linlin Li, Qun Liu, Yaqian Zhou, Xuanjing Huang, Xipeng Qiu. Arxiv 2025.

20. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models. Qiguang Chen, Libo Qin, Jinhao Liu, Dengyun Peng, Jiannan Guan, Peng Wang, Mengkang Hu, Yuhang Zhou, Te Gao, Wanxiang Che. Arxiv 2025.

21. A Comprehensive Survey on Long Context Language Modeling. Jiaheng Liu, Dawei Zhu, Zhiqi Bai, Yancheng He, Huanxuan Liao, Haoran Que, Zekun Wang, Chenchen Zhang, Ge Zhang, Jiebin Zhang, Yuanxing Zhang, Zhuo Chen, Hangyu Guo, Shilong Li, Ziqiang Liu, Yong Shan, Yifan Song, Jiayi Tian, Wenhao Wu, Zhejian Zhou, Ruijie Zhu, Junlan Feng, Yang Gao, Shizhu He, Zhoujun Li, Tianyu Liu, Fanyu Meng, Wenbo Su, Yingshui Tan, Zili Wang, Jian Yang, Wei Ye, Bo Zheng, Wangchunshu Zhou, Wenhao Huang, Sujian Li, Zhaoxiang Zhang. Arxiv 2025.

22. Technologies on Effectiveness and Efficiency: A Survey of State Spaces Models. Xingtai Lv, Youbang Sun, Kaiyan Zhang, Shang Qu, Xuekai Zhu, Yuchen Fan, Yi Wu, Ermo Hua, Xinwei Long, Ning Ding, Bowen Zhou. Arxiv 2025.

23. A Survey on Knowledge-Oriented Retrieval-Augmented Generation. Mingyue Cheng, Yucong Luo, Jie Ouyang, Qi Liu, Huijie Liu, Li Li, Shuo Yu, Bohou Zhang, Jiawei Cao, Jie Ma, Daoyu Wang. Arxiv 2025.

24. Key, Value, Compress: A Systematic Exploration of KV Cache Compression Techniques. Neusha Javidnia, Bita Darvish Rouhani, Farinaz Koushanfar. Arxiv 2025.

25. A Survey on Transformer Context Extension: Approaches and Evaluation. Yijun Liu, Jinzheng Yu, Yang Xu, Zhongyang Li, Qingfu Zhu. Arxiv 2025.

26. Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models. Yang Sui, Yu-Neng Chuang, Guanchu Wang, Jiamu Zhang, Tianyi Zhang, Jiayi Yuan, Hongyi Liu, Andrew Wen, Shaochen Zhong, Hanjie Chen, Xia Hu. Arxiv 2025.

27. A Survey on Structured State Space Sequence (S4) Models. Shriyank Somvanshi, Md Monzurul Islam, Mahmuda Sultana Mimi, Sazzad Bin Bashar Polock, Gaurab Chhetri, Subasish Das. Arxiv 2025.

28. A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond. Xiaoye Qu, Yafu Li, Zhaochen Su, Weigao Sun, Jianhao Yan, Dongrui Liu, Ganqu Cui, Daizong Liu, Shuxian Liang, Junxian He, Peng Li, Wei Wei, Jing Shao, Chaochao Lu, Yue Zhang, Xian-Sheng Hua, Bowen Zhou, Yu Cheng. Arxiv 2025.

29. Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models. Rui Wang, Hongru Wang, Boyang Xue, Jianhui Pang, Shudong Liu, Yi Chen, Jiahao Qiu, Derek Fai Wong, Heng Ji, Kam-Fai Wong. Arxiv 2025.

30. Efficient Inference for Large Reasoning Models: A Survey. Yue Liu, Jiaying Wu, Yufei He, Hongcheng Gao, Hongyu Chen, Baolong Bi, Jiaheng Zhang, Zhiqi Huang, Bryan Hooi. Arxiv 2025.

31. A Survey on Inference Engines for Large Language Models: Perspectives on Optimization and Efficiency. Sihyeong Park, Sungryeol Jeon, Chaelyn Lee, Seokhun Jeon, Byung-Soo Kim, Jemin Lee. Arxiv 2025.

32. Optimizing LLMs for Resource-Constrained Environments: A Survey of Model Compression Techniques. Sanjay Surendranath Girija, Shashank Kapoor, Lakshit Arora, Dipen Pradhan, Aman Raj, Ankit Shetgaonkar. IEEE COMPSAC 2025.

33. Shifting AI Efficiency From Model-Centric to Data-Centric Compression. Xuyang Liu, Zichen Wen, Shaobo Wang, Junjie Chen, Zhishan Tao, Yubo Wang, Xiangqi Jin, Chang Zou, Yiyu Wang, Chenfei Liao, Xu Zheng, Honggang Chen, Weijia Li, Xuming Hu, Conghui He, Linfeng Zhang. Arxiv 2025.

34. Speed Always Wins: A Survey on Efficient Architectures for Large Language Models. Weigao Sun, Jiaxi Hu, Yucheng Zhou, Jusen Du, Disen Lan, Kexin Wang, Tong Zhu, Xiaoye Qu, Yu Zhang, Xiaoyu Mo, Daizong Liu, Yuxuan Liang, Wenliang Chen, Guoqi Li, Yu Cheng. Arxiv 2025.

35. Speed Always Wins: A Survey on Efficient Architectures for Large Language Models. Xinda Jia, Jinpeng Li, Zezhong Wang, Jingjing Li, Xingshan Zeng, Yasheng Wang, Weinan Zhang, Yong Yu, Weiwen Liu. Arxiv 2025.

36. Explain Before You Answer: A Survey on Compositional Visual Reasoning. Fucai Ke, Joy Hsu, Zhixi Cai, Zixian Ma, Xin Zheng, Xindi Wu, Sukai Huang, Weiqing Wang, Pari Delir Haghighi, Gholamreza Haffari, Ranjay Krishna, Jiajun Wu, Hamid Rezatofighi. Arxiv 2025.

37. Video-LMM Post-Training: A Deep Dive into Video Reasoning with Large Multimodal Models. Yolo Yunlong Tang, Jing Bi, Pinxin Liu, Zhenyu Pan, Zhangyun Tan, Qianxiang Shen, Jiani Liu, Hang Hua, Junjia Guo, Yunzhong Xiao, Chao Huang, Zhiyuan Wang, Susan Liang, Xinyi Liu, Yizhi Song, Yuhe Nie, Jia-Xing Zhong, Bozheng Li, Daiqing Qi, Ziyun Zeng, Ali Vosoughi, Luchuan Song, Zeliang Zhang, Daiki Shimada, Han Liu, Jiebo Luo, Chenliang Xu. Arxiv 2025.

2. Efficient Attention

2.1 Sparse Attention

1. Generating Long Sequences with Sparse Transformers. Rewon Child, Scott Gray, Alec Radford, Ilya Sutskever. Arxiv 2019.

2. Blockwise selfattention for long document understanding. Jiezhong Qiu, Hao Ma, Omer Levy, Wen-tau Yih, Sinong Wang, Jie Tang. EMNLP 2020.

3. Longformer: The Long-Document Transformer. Iz Beltagy, Matthew E. Peters, Arman Cohan. Arxiv 2020.

4. ETC: Encoding Long and Structured Inputs in Transformers. Joshua Ainslie, Santiago Ontanon, Chris Alberti, Vaclav Cvicek, Zachary Fisher, Philip Pham, Anirudh Ravula, Sumit Sanghai, Qifan Wang, Li Yang. EMNLP 2020.

5. Big Bird: Transformers for Longer Sequences. Manzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, Amr Ahmed. NeurIPS 2020.

6. Reformer: The efficient transformer. Nikita Kitaev, Łukasz Kaiser, Anselm Levskaya. ICLR 2020.

7. Sparse Sinkhorn Attention. Yi Tay, Dara Bahri, Liu Yang, Donald Metzler, Da-Cheng Juan. ICML 2020.

8. Sparse and continuous attention mechanisms. André F. T. Martins, António Farinhas, Marcos Treviso, Vlad Niculae, Pedro M. Q. Aguiar, Mário A. T. Figueiredo. NIPS 2020.

9. Efficient Content-Based Sparse Attention with Routing Transformers. Aurko Roy, Mohammad Saffar, Ashish Vaswani, David Grangier. TACL 2021.

10. LongT5: Efficient text-to-text transformer for long sequences. Mandy Guo, Joshua Ainslie, David Uthus, Santiago Ontanon, Jianmo Ni, Yun-Hsuan Sung, Yinfei Yang. NAACL 2022.

11. Efficient Long-Text Understanding with Short-Text Models. Maor Ivgi, Uri Shaham, Jonathan Berant. TACL 2023.

12. Parallel Context Windows for Large Language Models. Nir Ratner, Yoav Levine, Yonatan Belinkov, Ori Ram, Inbal Magar, Omri Abend, Ehud Karpas, Amnon Shashua, Kevin Leyton-Brown, Yoav Shoham. ACL 2023.

13. Unlimiformer: Long-Range Transformers with Unlimited Length Input. Amanda Bertsch, Uri Alon, Graham Neubig, Matthew R. Gormley. Arxiv 2023.

14. Landmark Attention: Random-Access Infinite Context Length for Transformers. Amirkeivan Mohtashami, Martin Jaggi Arxiv 2023.

15. LONGNET: Scaling Transformers to 1,000,000,000 Tokens. Jiayu Ding, Shuming Ma, Li Dong, Xingxing Zhang, Shaohan Huang, Wenhui Wang, Nanning Zheng, Furu Wei. Arxiv 2023.

16. Adapting Language Models to Compress Contexts. Alexis Chevalier, Alexander Wettig, Anirudh Ajith, Danqi Chen. Arxiv 2023.

17. Blockwise Parallel Transformer for Long Context Large Models. Hao Liu, Pieter Abbeel. Arxiv 2023.

18. MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers. Lili Yu, Dániel Simig, Colin Flaherty, Armen Aghajanyan, Luke Zettlemoyer, Mike Lewis. Arxiv 2023.

19. Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers. Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurelien Lucchi, Thomas Hofmann. Arxiv 2023.

20. Long-range Language Modeling with Self-retrieval. Ohad Rubin, Jonathan Berant. Arxiv 2023.

21. Max-Margin Token Selection in Attention Mechanism. Davoud Ataee Tarzanagh, Yingcong Li, Xuechen Zhang, Samet Oymak. Arxiv 2023.

22. Chunk, Align, Select: A Simple Long-sequence Processing Method for Transformers. Jiawen Xie, Pengyu Cheng, Xiao Liang, Yong Dai, Nan Du. Arxiv 2023.

23. Sparse Token Transformer with Attention Back Tracking. Heejun Lee, Minki Kang, Youngwan Lee, Sung Ju Hwang. ICLR 2023.

24. Empower Your Model with Longer and Better Context Comprehension. YiFei Gao, Lei Wang, Jun Fang, Longhua Hu, Jun Cheng. Arxiv 2023.

25. Ring Attention with Blockwise Transformers for Near-Infinite Context. Hao Liu, Matei Zaharia, Pieter Abbeel. Arxiv 2023.

26. Efficient Streaming Language Models with Attention Sinks. Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, Mike Lewis. Arxiv 2023.

27. HyperAttention: Long-context Attention in Near-Linear Time. Insu Han, Rajesh Jayaram, Amin Karbasi, Vahab Mirrokni, David P. Woodruff, Amir Zandieh. Arxiv 2023.

28. Fovea Transformer: Efficient Long-Context Modeling with Structured Fine-to-Coarse Attention. Ziwei He,Jian Yuan,Le Zhou,Jingwen Leng,Bo Jiang. Arxiv 2023.

29. ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition. Lu Ye, Ze Tao, Yong Huang, Yang Li. Arxiv 2024.

30. Training-Free Long-Context Scaling of Large Language Models. Chenxin An, Fei Huang, Jun Zhang, Shansan Gong, Xipeng Qiu, Chang Zhou, Lingpeng Kong. Arxiv 2024.

31. LongHeads: Multi-Head Attention is Secretly a Long Context Processor. Yi Lu, Xin Zhou, Wei He, Jun Zhao, Tao Ji, Tao Gui, Qi Zhang, Xuanjing Huang. Arxiv 2024.

32. Zebra: Extending Context Window with Layerwise Grouped Local-Global Attention. Kaiqiang Song, Xiaoyang Wang, Sangwoo Cho, Xiaoman Pan, Dong Yu. Arxiv 2023.

33. SnapKV: LLM Knows What You are Looking for Before Generation. Yuhong Li, Yingbing Huang, Bowen Yang, Bharat Venkitesh, Acyr Locatelli, Hanchen Ye, Tianle Cai, Patrick Lewis, Deming Chen. Arxiv 2024.

34. Sequence can Secretly Tell You What to Discard. Jincheng Dai, Zhuowei Huang, Haiyun Jiang, Chen Chen, Deng Cai, Wei Bi, Shuming Shi. Arxiv 2024.

35. SinkLoRA: Enhanced Efficiency and Chat Capabilities for Long-Context Large Language Models. Hengyu Zhang. Arxiv 2024.

36. HiP Attention: Sparse Sub-Quadratic Attention with Hierarchical Attention Pruning. Heejun Lee, Geon Park, Youngwan Lee, Jina Kim, Wonyoung Jeong, Myeongjae Jeon, Sung Ju Hwang. Arxiv 2024.

37. Taking a Deep Breath: Enhancing Language Modeling of Large Language Models with Sentinel Tokens. Weiyao Luo, Suncong Zheng, Heming Xia, Weikang Wang, Yan Lei, Tianyu Liu, Shuang Chen, Zhifang Sui. Arxiv 2024.

38. MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression. Weiyao Luo, Suncong Zheng, Heming Xia, Weikang Wang, Yan Lei, Tianyu Liu, Shuang Chen, Zhifang Sui. Arxiv 2024.

39. Sparser is Faster and Less is More: Efficient Sparse Attention for Long-Range Transformers. Chao Lou, Zixia Jia, Zilong Zheng, Kewei Tu. Arxiv 2024.

40. Near-Lossless Acceleration of Long Context LLM Inference with Adaptive Structured Sparse Attention. Qianchao Zhu, Jiangfei Duan, Chang Chen, Siran Liu, Xiuhong Li, Guanyu Feng, Xin Lv, Huanqi Cao, Xiao Chuanfu, Xingcheng Zhang, Dahua Lin, Chao Yang. Arxiv 2024.

41. Neurocache: Efficient Vector Retrieval for Long-range Language Modeling. Ali Safaya, Deniz Yuret. Arxiv 2024.

42. Weighted Grouped Query Attention in Transformers. Sai Sena Chinnakonduru, Astarag Mohapatra. Arxiv 2024.

43. Selective Attention Improves Transformer. Yaniv Leviathan, Matan Kalman, Yossi Matias. Arxiv 2024.

44. TidalDecode: Fast and Accurate LLM Decoding with Position Persistent Sparse Attention. Lijie Yang, Zhihao Zhang, Zhuofu Chen, Zikun Li, Zhihao Jia. Arxiv 2024.

45. FltLM: An Intergrated Long-Context Large Language Model for Effective Context Filtering and Understanding. Jingyang Deng, Zhengyang Shen, Boyang Wang, Lixin Su, Suqi Cheng, Ying Nie, Junfeng Wang, Dawei Yin, Jinwen Ma. Arxiv 2024.

46. Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix. Yingyu Liang, Jiangxuan Long, Zhenmei Shi, Zhao Song, Yufa Zhou. Arxiv 2024.

47. Extra Global Attention Designation Using Keyword Detection in Sparse Transformer Architectures. Evan Lucas, Dylan Kangas, Timothy C Havens. Arxiv 2024.

48. SeerAttention: Learning Intrinsic Sparse Attention in Your LLMs. Yizhao Gao, Zhichen Zeng, Dayou Du, Shijie Cao, Hayden Kwok-Hay So, Ting Cao, Fan Yang, Mao Yang. Arxiv 2024.

49. Selective Attention: Enhancing Transformer through Principled Context Control. Xuechen Zhang, Xiangyu Chang, Mingchen Li, Amit Roy-Chowdhury, Jiasi Chen, Samet Oymak. NeurIPS 2024.

50. Core Context Aware Attention for Long Context Language Modeling. Yaofo Chen, Zeng You, Shuhai Zhang, Haokun Li, Yirui Li, Yaowei Wang, Mingkui Tan. Arxiv 2024.

51. Inference-time sparse attention with asymmetric indexing. Pierre-Emmanuel Mazaré, Gergely Szilvasy, Maria Lomeli, Francisco Massa, Naila Murray, Hervé Jégou, Matthijs Douze. Arxiv 2025.

52. Top-Theta Attention: Sparsifying Transformers by Compensated Thresholding. Konstantin Berestizshevsky, Renzo Andri, Lukas Cavigelli. Arxiv 2025.

53. MoBA: Mixture of Block Attention for Long-Context LLMs. Enzhe Lu, Zhejun Jiang, Jingyuan Liu, Yulun Du, Tao Jiang, Chao Hong, Shaowei Liu, Weiran He, Enming Yuan, Yuzhi Wang, Zhiqi Huang, Huan Yuan, Suting Xu, Xinran Xu, Guokun Lai, Yanru Chen, Huabin Zheng, Junjie Yan, Jianlin Su, Yuxin Wu, Neo Y. Zhang, Zhilin Yang, Xinyu Zhou, Mingxing Zhang, Jiezhong Qiu. Arxiv 2025.

54. Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention. Jingyang Yuan, Huazuo Gao, Damai Dai, Junyu Luo, Liang Zhao, Zhengyan Zhang, Zhenda Xie, Y. X. Wei, Lean Wang, Zhiping Xiao, Yuqing Wang, Chong Ruan, Ming Zhang, Wenfeng Liang, Wangding Zeng. Arxiv 2025.

55. Neural Attention Search. Difan Deng, Marius Lindauer. Arxiv 2025.

56. PowerAttention: Exponentially Scaling of Receptive Fields for Effective Sparse Attention. Lida Chen, Dong Xu, Chenxin An, Xintao Wang, Yikai Zhang, Jiangjie Chen, Zujie Liang, Feng Wei, Jiaqing Liang, Yanghua Xiao, Wei Wang. Arxiv 2025.

57. Cost-Optimal Grouped-Query Attention for Long-Context LLMs. Yingfa Chen, Yutong Wu, Xu Han, Zhiyuan Liu, Maosong Sun. Arxiv 2025.

58. X-EcoMLA: Upcycling Pre-Trained Attention into MLA for Efficient and Extreme KV Compression. Guihong Li, Mehdi Rezagholizadeh, Mingyu Yang, Vikram Appia, Emad Barsoum. Arxiv 2025.

59. OmniKV: Dynamic Context Selection for Efficient Long-Context LLMs Jitai Hao, Yuke Zhu, Tian Wang, Jun Yu, Xin Xin, Bo Zheng, Zhaochun Ren, Sheng Guo. ICLR 2025.

60. XAttention: Block Sparse Attention with Antidiagonal Scoring. Ruyi Xu, Guangxuan Xiao, Haofeng Huang, Junxian Guo, Song Han. Arxiv 2025.

61. The Sparse Frontier: Sparse Attention Trade-offs in Transformer LLMs. Piotr Nawrot, Robert Li, Renjie Huang, Sebastian Ruder, Kelly Marchisio, Edoardo M. Ponti. Arxiv 2025.

62. Mixture of Sparse Attention: Content-Based Learnable Sparse Attention via Expert-Choice Routing. Piotr Piękos, Róbert Csordás, Jürgen Schmidhuber. Arxiv 2025.

63. Multi-head Temporal Latent Attention. Keqi Deng, Philip C. Woodland. Arxiv 2025.

64. Scale-invariant Attention. Ben Anson, Xi Wang, Laurence Aitchison. Arxiv 2025.

65. SageAttention2++: A More Efficient Implementation of SageAttention2. Jintao Zhang, Xiaoming Xu, Jia Wei, Haofeng Huang, Pengle Zhang, Chendong Xiang, Jun Zhu, Jianfei Chen. Arxiv 2025.

66. HATA: Trainable and Hardware-Efficient Hash-Aware Top-k Attention for Scalable Large Model Inference. Ping Gong, Jiawei Yi, Shengnan Wang, Juncheng Zhang, Zewen Jin, Ouxiang Zhou, Ruibo Liu, Guanbin Xu, Youhui Bai, Bowen Ye, Kun Yuan, Tong Yang, Gong Zhang, Renhai Chen, Feng Wu, Cheng Li. Arxiv 2025.

67. Rectified Sparse Attention. Yutao Sun, Tianzhu Ye, Li Dong, Yuqing Xia, Jian Chen, Yizhao Gao, Shijie Cao, Jianyong Wang, Furu Wei. Arxiv 2025.

68. SeerAttention-R: Sparse Attention Adaptation for Long Reasoning. Yizhao Gao, Shuming Guo, Shijie Cao, Yuqing Xia, Yu Cheng, Lei Wang, Lingxiao Ma, Yutao Sun, Tianzhu Ye, Li Dong, Hayden Kwok-Hay So, Yu Hua, Ting Cao, Fan Yang, Mao Yang. Arxiv 2025.

69. Lag-Relative Sparse Attention In Long Context Training. Manlai Liang, Wanyi Huang, Mandi Liu, Huaijun Li, Jinlong Li. Arxiv 2025.

70. DAM: Dynamic Attention Mask for Long-Context Large Language Model Inference Acceleration. Hanzhi Zhang, Heng Fan, Kewei Sha, Yan Huang, Yunhe Feng. Arxiv 2025.

71. GTA: Grouped-head latenT Attention. Luoyang Sun, Jiwen Jiang, Cheng Deng, Xinjian Wu, Haifeng Zhang, Lei Chen, Lionel Ni, Jun Wang. Arxiv 2025.

72. Fast and Simplex: 2-Simplicial Attention in Triton. Aurko Roy, Timothy Chou, Sai Surya Duvvuri, Sijia Chen, Jiecao Yu, Xiaodong Wang, Manzil Zaheer, Rohan Anil. Arxiv 2025.

73. TriangleMix: A Lossless and Efficient Attention Pattern for Long Context Prefilling. Zhiyuan He, Yike Zhang, Chengruidong Zhang, Huiqiang Jiang, Yuqing Yang, Lili Qiu. Arxiv 2025.

74. Trainable Dynamic Mask Sparse Attention. Jingze Shi, Yifan Wu, Bingheng Wu, Yiran Peng, Liangdong Wang, Guang Liu, Yuyu Luo. Arxiv 2025.

75. Less Is More: Training-Free Sparse Attention with Global Locality for Efficient Reasoning. Lijie Yang, Zhihao Zhang, Arti Jain, Shijie Cao, Baihong Yuan, Yiwei Chen, Zhihao Jia, Ravi Netravali. Arxiv 2025.

76. Elastic Attention: Test-time Adaptive Sparsity Ratios for Efficient Transformers. Zecheng Tang, Quantong Qiu, Yi Yang, Zhiyi Hong, Haiya Xiang, Kebin Liu, Qingqing Dang, Juntao Li, Min Zhang. Arxiv 2026.

2.2 Linear Attention

1. Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention. Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas, François Fleuret. ICML 2020.

2. Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations. Tri Dao, Albert Gu, Matthew Eichhorn, Atri Rudra, Christopher Ré. Arxiv 2019.

3. Masked language modeling for proteins via linearly scalable long-context transformers. Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Davis, David Belanger, Lucy Colwell, Adrian Weller. Arxiv 2020.

4. Rethinking attention with performers. Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy Colwell, Adrian Weller. Arxiv 2020.

5. Linformer: Self-attention with linear complexity. Sinong Wang, Belinda Z. Li, Madian Khabsa, Han Fang, Hao Ma. Arxiv 2020.

6. Random Feature Attention. Hao Peng, Nikolaos Pappas, Dani Yogatama, Roy Schwartz, Noah A. Smith, Lingpeng Kong. Arxiv 2021.

7. Luna: Linear unified nested attention. Xuezhe Ma, Xiang Kong, Sinong Wang, Chunting Zhou, Jonathan May, Hao Ma, Luke Zettlemoyer. Arxiv 2021.

8. Fnet: Mixing tokens with fourier transforms. James Lee-Thorp, Joshua Ainslie, Ilya Eckstein, Santiago Ontanon. Arxiv 2021.

9. Gated Linear Attention Transformers with Hardware-Efficient Training. Songlin Yang, Bailin Wang, Yikang Shen, Rameswar Panda, Yoon Kim. Arxiv 2023.

10. Latent Attention for Linear Time Transformers. Rares Dolga, Marius Cobzarenco, David Barber. Arxiv 2024.

11. Simple linear attention language models balance the recall-throughput tradeoff. Simran Arora, Sabri Eyuboglu, Michael Zhang, Aman Timalsina, Silas Alberti, Dylan Zinsley, James Zou, Atri Rudra, Christopher Ré. Arxiv 2024.

12. Linear Attention Sequence Parallelism. Weigao Sun, Zhen Qin, Dong Li, Xuyang Shen, Yu Qiao, Yiran Zhong. Arxiv 2024.

13. Softmax Attention with Constant Cost per Token. Franz A. Heinsen. Arxiv 2024. ![GitHub Repo stars](https://img.shields.io/github/stars/glassroom/heinsen_attention

14. Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length. Xuezhe Ma, Xiaomeng Yang, Wenhan Xiong, Beidi Chen, Lili Yu, Hao Zhang, Jonathan May, Luke Zettlemoyer, Omer Levy, Chunting Zhou. Arxiv 2024. ![GitHub Repo stars](https://img.shields.io/github/stars/XuezheMax/megalodon

15. Various Lengths, Constant Speed: Efficient Language Modeling with Lightning Attention. Zhen Qin, Weigao Sun, Dong Li, Xuyang Shen, Weixuan Sun, Yiran Zhong. Arxiv 2024.

16. Unlocking the Secrets of Linear Complexity Sequence Model from A Unified Perspective. Zhen Qin, Xuyang Shen, Weigao Sun, Dong Li, Stan Birchfield, Richard Hartley, Yiran Zhong. Arxiv 2024.

17. Attention as an RNN. Leo Feng, Frederick Tung, Hossein Hajimirsadeghi, Mohamed Osama Ahmed, Yoshua Bengio, Greg Mori. Arxiv 2024.

18. You Only Scan Once: Efficient Multi-dimension Sequential Modeling with LightNet. Zhen Qin, Yuxin Mao, Xuyang Shen, Dong Li, Jing Zhang, Yuchao Dai, Yiran Zhong. Arxiv 2024. ![GitHub Repo stars](https://img.shields.io/github/stars/OpenNLPLab/LightNet

19. When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models. Haoran You, Yichao Fu, Zheng Wang, Amir Yazdanbakhsh, Yingyan (Celine)Lin. Arxiv 2024. ![GitHub Repo stars](https://img.shields.io/github/stars/GATECH-EIC/Linearized-LLM

20. Learning to (Learn at Test Time): RNNs with Expressive Hidden States. Yu Sun, Xinhao Li, Karan Dalal, Jiarui Xu, Arjun Vikram, Genghan Zhang, Yann Dubois, Xinlei Chen, Xiaolong Wang, Sanmi Koyejo, Tatsunori Hashimoto, Carlos Guestrin. Arxiv 2024. ![GitHub Repo stars](https://img.shields.io/github/stars/test-time-training/ttt-lm-pytorch         ![GitHub Repo stars](https://img.shields.io/github/stars/test-time-training/ttt-lm-jax

21. Gated Slot Attention for Efficient Linear-Time Sequence Modeling. Yu Zhang, Songlin Yang, Ruijie Zhu, Yue Zhang, Leyang Cui, Yiqiao Wang, Bolun Wang, Freda Shi, Bailin Wang, Wei Bi, Peng Zhou, Guohong Fu. Arxiv 2024. ![GitHub Repo stars](https://img.shields.io/github/stars/sustcsonglin/flash-linear-attention

22. LASP-2: Rethinking Sequence Parallelism for Linear Attention and Its Hybrid. Weigao Sun, Disen Lan, Yiran Zhong, Xiaoye Qu, Yu Cheng. Arxiv 2025. ![GitHub Repo stars](https://img.shields.io/github/stars/OpenSparseLLMs/Linear-MoE

23. MoM: Linear Sequence Modeling with Mixture-of-Memories. Jusen Du, Weigao Sun, Disen Lan, Jiaxi Hu, Yu Cheng. Arxiv 2025. ![GitHub Repo stars](https://img.shields.io/github/stars/OpenSparseLLMs/MoM

24. EDiT: Efficient Diffusion Transformers with Linear Compressed Attention. Philipp Becker, Abhinav Mehrotra, Ruchika Chavhan, Malcolm Chadwick, Luca Morreale, Mehdi Noroozi, Alberto Gil Ramos, Sourav Bhattacharya. Arxiv 2025.

25. LoLA: Low-Rank Linear Attention With Sparse Caching. Luke McDermott, Robert W. Heath Jr., Rahul Parhi. Arxiv 2025.

26. Every Attention Matters: An Efficient Hybrid Architecture for Long-Context Reasoning. Ling Team, Bin Han, Caizhi Tang, Chen Liang, Donghao Zhang, Fan Yuan, Feng Zhu, Jie Gao, Jingyu Hu, Longfei Li, Meng Li, Mingyang Zhang, Peijie Jiang, Peng Jiao, Qian Zhao, Qingyuan Yang, Wenbo Shen, Xinxing Yang, Yalin Zhang, Yankun Ren, Yao Zhao, Yibo Cao, Yixuan Sun, Yue Zhang, Yuchen Fang, Zibin Lin, Zixuan Cheng, Jun Zhou. Arxiv 2025.

27. Alleviating Forgetfulness of Linear Attention by Hybrid Sparse Attention and Contextualized Learnable Token Eviction. Mutian He, Philip N. Garner. Arxiv 2025.

28. MHLA: Restoring Expressivity of Linear Attention via Token-Level Multi-Head. Kewei Zhang, Ye Huang, Yufan Deng, Jincheng Yu, Junsong Chen, Huan Ling, Enze Xie, Daquan Zhou. Arxiv 2026.

2.3 Hierarchical Attention

1. Neural Legal Judgment Prediction in English. Ilias Chalkidis, Ion Androutsopoulos, Nikolaos Aletras. ACL 2019.

2. Hierarchical Neural Network Approaches for Long Document Classification. Snehal Khandve, Vedangi Wagh, Apurva Wani, Isha Joshi, Raviraj Joshi. ICML 2022.

3. Hi-transformer: Hierarchical interactive transformer for efficient and effective long document modeling. Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang. ACL-IJCNLP 2021

4. Erniesparse: Learning hierarchical efficient transformer through regularized self-attention. Yang Liu, Jiaxiang Liu, Li Chen, Yuxiang Lu, Shikun Feng, Zhida Feng, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang. Arxiv 2022.

2.4 IO-Aware Attention

1. Self-attention Does Not Need O(n^2) Memory. Markus N. Rabe, Charles Staats. Arxiv 2021.

2. Faster Causal Attention Over Large Sequences Through Sparse Flash Attention. Matteo Pagliardini, Daniele Paliotta, Martin Jaggi, François Fleuret. Arxiv 2023.

3. FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness. Tri Dao, Daniel Y. Fu, Stefano Ermon, Atri Rudra, Christopher Ré. Arxiv 2022.

4. FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning. Tri Dao. Arxiv 2023.

5. Efficient Memory Management for Large Language Model Serving with PagedAttention. Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, Ion Stoica. Arxiv 2023.

6. TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer. Zhen Qin, Dong Li, Weigao Sun, Weixuan Sun, Xuyang Shen, Xiaodong Han, Yunshen Wei, Baohong Lv, Xiao Luo, Yu Qiao, Yiran Zhong. Arxiv 2023.

7. Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models. Zhen Qin, Weigao Sun, Dong Li, Xuyang Shen, Weixuan Sun, Yiran Zhong. Arxiv 2024.

8. ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition. Lu Ye, Ze Tao, Yong Huang, Yang Li. Arxiv 2024.

9. SnapKV: LLM Knows What You are Looking for Before Generation. Yuhong Li, Yingbing Huang, Bowen Yang, Bharat Venkitesh, Acyr Locatelli, Hanchen Ye, Tianle Cai, Patrick Lewis, Deming Chen. Arxiv 2024.

10. Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs. Suyu Ge, Yunan Zhang, Liyuan Liu, Minjia Zhang, Jiawei Han, Jianfeng Gao. ICLR 2024 Oral.

11. Keyformer: KV Cache Reduction through Key Tokens Selection for Efficient Generative Inference. Muhammad Adnan, Akhil Arunkumar, Gaurav Jain, Prashant J. Nair, Ilya Soloveychik, Purushotham Kamath. Arxiv 2024.

12. Efficient LLM Inference with Kcache. Qiaozhi He, Zhihua Wu. Arxiv 2024.

13. You Only Cache Once: Decoder-Decoder Architectures for Language Models. Yutao Sun, Li Dong, Yi Zhu, Shaohan Huang, Wenhui Wang, Shuming Ma, Quanlu Zhang, Jianyong Wang, Furu Wei. Arxiv 2024.

14. Fast Transformer Decoding: One Write-Head is All You Need. Noam Shazeer. Arxiv 2019.

15. GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints. Joshua Ainslie, James Lee-Thorp, Michiel de Jong, Yury Zemlyanskiy, Federico Lebrón, Sumit Sanghai. Arxiv 2023.

16. DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model. DeepSeek-AI. Arxiv 2024.

17. Layer-Condensed KV Cache for Efficient Inference of Large Language Models. Haoyi Wu, Kewei Tu. ACL 2024.

18. Reducing Transformer Key-Value Cache Size with Cross-Layer Attention. William Brandon, Mayank Mishra, Aniruddha Nrusimha, Rameswar Panda, Jonathan Ragan Kelly. Arxiv 2024.

19. PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM Inference. William Brandon, Mayank Mishra, Aniruddha Nrusimha, Rameswar Panda, Jonathan Ragan Kelly. Arxiv 2024.

20. Unlocking Data-free Low-bit Quantization with Matrix Decomposition for KV Cache Compression. Peiyu Liu, Ze-Feng Gao, Wayne Xin Zhao, Yipeng Ma, Tao Wang, Ji-Rong Wen. Arxiv 2024.

21. MiniCache: KV Cache Compression in Depth Dimension for Large Language Models. Akide Liu, Jing Liu, Zizheng Pan, Yefei He, Gholamreza Haffari, Bohan Zhuang. NeurIPS 2024.

22. PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling. Zefan Cai., Yichi Zhang, Bofei Gao, Tianyu Liu, Keming Lu, Wayne Xiong, Yue Dong, Baobao Chang, Junjie Hu, Wen Xiao. Arxiv 2024.

23. Effectively Compress KV Heads for LLM. Hao Yu, Zelan Yang, Shen Li, Yong Li, Jianxin Wu. Arxiv 2024.

24. A Simple and Effective L2 Norm-Based Strategy for KV Cache Compression. Alessio Devoto, Yu Zhao, Simone Scardapane, Pasquale Minervini. Arxiv 2024.

25. Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference. Jiaming Tang, Yilong Zhao, Kan Zhu, Guangxuan Xiao, Baris Kasikci, Song Han. ICML 2024.

26. Attention Score is not All You Need for Token Importance Indicator in KV Cache Reduction: Value Also Matters. Zhiyu Guo, Hidetaka Kamigaito, Taro Watanabe. Arxiv 2024.

27. CItruS: Chunked Instruction-aware State Eviction for Long Sequence Modeling. Yu Bai, Xiyuan Zou, Heyan Huang, Sanxing Chen, Marc-Antoine Rondeau, Yang Gao, Jackie Chi Kit Cheung. Arxiv 2024.

28. D2O: Dynamic Discriminative Operations for Efficient Generative Inference of Large Language Models. Zhongwei Wan, Xinjian Wu, Yu Zhang, Yi Xin, Chaofan Tao, Zhihong Zhu, Xin Wang, Siqi Luo, Jing Xiong, Mi Zhang. Arxiv 2024.

29. MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression. Weiyao Luo, Suncong Zheng, Heming Xia, Weikang Wang, Yan Lei, Tianyu Liu, Shuang Chen, Zhifang Sui. Arxiv 2024.

30. LOOK-M: Look-Once Optimization in KV Cache for Efficient Multimodal Long-Context Inference. Zhongwei Wan, Ziang Wu, Che Liu, Jinfa Huang, Zhihong Zhu, Peng Jin, Longyue Wang, Li Yuan. Arxiv 2024.

31. Training-Free Exponential Extension of Sliding Window Context with Cascading KV Cache. Jeffrey Willette, Heejun Lee, Youngwan Lee, Myeongjae Jeon, Sung Ju Hwang. Arxiv 2024.

32. QuickLLaMA: Query-aware Inference Acceleration for Large Language Models. Jingyao Li, Han Shi, Xin Jiang, Zhenguo Li, Hong Xu, Jiaya Jia. Arxiv 2024.

33. MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention. Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, Qianhui Wu, Xufang Luo, Surin Ahn, Zhenhua Han, Amir H. Abdi, Dongsheng Li, Chin-Yew Lin, Yuqing Yang, Lili Qiu. Arxiv 2024.        

34. Model Tells You Where to Merge: Adaptive KV Cache Merging for LLMs on Long-Context Tasks. Zheng Wang, Boxiao Jin, Zhongzhi Yu, Minjia Zhang. Arxiv 2024.

35. Optimizing KV Cache Eviction in LLMs: Adaptive Allocation for Enhanced Budget Utilization. Yuan Feng, Junlin Lv, Yukun Cao, Xike Xie, S. Kevin Zhou. Arxiv 2024.

36. Beyond KV Caching: Shared Attention for Efficient LLMs. Bingli Liao, Danilo Vasconcellos Vargas. Arxiv 2024.

37. PQCache: Product Quantization-based KVCache for Long Context LLM Inference. Hailin Zhang, Xiaodong Ji, Yilin Chen, Fangcheng Fu, Xupeng Miao, Xiaonan Nie, Weipeng Chen, Bin Cui. Arxiv 2024.

38. LazyLLM: Dynamic Token Pruning for Efficient Long Context LLM Inference. Qichen Fu, Minsik Cho, Thomas Merth, Sachin Mehta, Mohammad Rastegari, Mahyar Najibi. Arxiv 2024.

39. Farewell to Length Extrapolation, a Training-Free Infinite Context with Finite Attention Scope. Xiaoran Liu, Qipeng Guo, Yuerong Song, Zhigeng Liu, Kai Lv, Hang Yan, Linlin Li, Qun Liu, Xipeng Qiu. Arxiv 2024.

40. RazorAttention: Efficient KV Cache Compression Through Retrieval Heads. Hanlin Tang, Yang Lin, Jing Lin, Qingsen Han, Shikuan Hong, Yiwu Yao, Gongyi Wang. Arxiv 2024.

41. FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision. Jay Shah, Ganesh Bikshandi, Ying Zhang, Vijay Thakkar, Pradeep Ramani, Tri Dao. Arxiv 2024.

42. ThinK: Thinner Key Cache by Query-Driven Pruning. Yuhui Xu, Zhanming Jie, Hanze Dong, Lei Wang, Xudong Lu, Aojun Zhou, Amrita Saha, Caiming Xiong, Doyen Sahoo. ICLR 2025.

43. A2SF: Accumulative Attention Scoring with Forgetting Factor for Token Pruning in Transformer Decoder. Hyun-rae Jo, Dongkun Shin. Arxiv 2024.

44. Cross-layer Attention Sharing for Large Language Models. Yongyu Mu, Yuzhang Wu, Yuchun Fan, Chenglong Wang, Hengyu Li, Qiaozhi He, Murun Yang, Tong Xiao, Jingbo Zhu. Arxiv 2024.

45. NACL: A General and Effective KV Cache Eviction Framework for LLMs at Inference Time. Yilong Chen, Guoxia Wang, Junyuan Shang, Shiyao Cui, Zhenyu Zhang, Tingwen Liu, Shuohuan Wang, Yu Sun, Dianhai Yu, Hua Wu. ACL 2024.

46. Tree Attention: Topology-aware Decoding for Long-Context Attention on GPU clusters. Vasudev Shyam, Jonathan Pilault, Emily Shepperd, Quentin Anthony, Beren Millidge. Arxiv 2024.

47. MagicDec: Breaking the Latency-Throughput Tradeoff for Long Context Generation with Speculative Decoding. Jian Chen, Vashisth Tiwari, Ranajoy Sadhukhan, Zhuoming Chen, Jinyuan Shi, Ian En-Hsu Yen, Beidi Chen. Arxiv 2024.

48. CSKV: Training-Efficient Channel Shrinking for KV Cache in Long-Context Scenarios. Luning Wang, Shiyao Li, Xuefei Ning, Zhihang Yuan, Shengen Yan, Guohao Dai, Yu Wang. Arxiv 2024.

49. RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval. Di Liu, Meng Chen, Baotong Lu, Huiqiang Jiang, Zhenhua Han, Qianxi Zhang, Qi Chen, Chengruidong Zhang, Bailu Ding, Kai Zhang, Chen Chen, Fan Yang, Yuqing Yang, Lili Qiu. Arxiv 2024.

50. InstInfer: In-Storage Attention Offloading for Cost-Effective Long-Context LLM Inference. Xiurui Pan, Endian Li, Qiao Li, Shengwen Liang, Yizhou Shan, Ke Zhou, Yingwei Luo, Xiaolin Wang, Jie Zhang. Arxiv 2024.

51. CritiPrefill: A Segment-wise Criticality-based Approach for Prefilling Acceleration in LLMs. Junlin Lv, Yuan Feng, Xike Xie, Xin Jia, Qirong Peng, Guiming Xie. Arxiv 2024.

52. Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token Reduction. Zhenmei Shi, Yifei Ming, Xuan-Phi Nguyen, Yingyu Liang, Shafiq Joty. Arxiv 2024.

53. Inference-Friendly Models With MixAttention. Shashank Rajput, Ying Sheng, Sean Owen, Vitaliy Chiley. Arxiv 2024.

54. KV-Compress: Paged KV-Cache Compression with Variable Compression Rates per Attention Head. Isaac Rehg. Arxiv 2024.

55. Locret: Enhancing Eviction in Long-Context LLM Inference with Trained Retaining Heads. Yuxiang Huang, Binhang Yuan, Xu Han, Chaojun Xiao, Zhiyuan Liu. Arxiv 2024.

56. InfiniPot: Infinite Context Processing on Memory-Constrained LLMs. Minsoo Kim, Kyuhong Shim, Jungwook Choi, Simyung Chang. Arxiv 2024.

57. UNComp: Uncertainty-Aware Long-Context Compressor for Efficient Large Language Model Inference. Jing Xiong, Jianghan Shen, Fanghua Ye, Chaofan Tao, Zhongwei Wan, Jianqiao Lu, Xun Wu, Chuanyang Zheng, Zhijiang Guo, Lingpeng Kong, Ngai Wong. Arxiv 2024.

58. LoRC: Low-Rank Compression for LLMs KV Cache with a Progressive Compression Strategy. Rongzhi Zhang, Kuang Wang, Liyuan Liu, Shuohang Wang, Hao Cheng, Chao Zhang, Yelong Shen. Arxiv 2024.

59. DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads. Guangxuan Xiao, Jiaming Tang, Jingwei Zuo, Junxian Guo, Shang Yang, Haotian Tang, Yao Fu, Song Han. Arxiv 2024.

60. In-context KV-Cache Eviction for LLMs via Attention-Gate. Zihao Zeng, Bokai Lin, Tianqi Hou, Hao Zhang, Zhijie Deng. Arxiv 2024.

61. SimLayerKV: A Simple Framework for Layer-Level KV Cache Reduction. Xuan Zhang, Cunxiao Du, Chao Du, Tianyu Pang, Wei Gao, Min Lin. Arxiv 2024.

62. A Systematic Study of Cross-Layer KV Sharing for Efficient LLM Inference. You Wu, Haoyi Wu, Kewei Tu. Arxiv 2024.

63. KVSharer: Efficient Inference via Layer-Wise Dissimilar KV Cache Sharing. Yifei Yang, Zouying Cao, Qiguang Chen, Libo Qin, Dongjie Yang, Hai Zhao, Zhi Chen. Arxiv 2024.

64. Lossless KV Cache Compression to 2%. Zhen Yang, J.N.Han, Kan Wu, Ruobing Xie, An Wang, Xingwu Sun, Zhanhui Kang. Arxiv 2024.

65. MatryoshkaKV: Adaptive KV Compression via Trainable Orthogonal Projection. Bokai Lin, Zihao Zeng, Zipeng Xiao, Siqi Kou, Tianqi Hou, Xiaofeng Gao, Hao Zhang, Zhijie Deng. Arxiv 2024.

66. EPIC: Efficient Position-Independent Context Caching for Serving Large Language Models. Junhao Hu, Wenrui Huang, Haoyi Wang, Weidong Wang, Tiancheng Hu, Qin Zhang, Hao Feng, Xusheng Chen, Yizhou Shan, Tao Xie. Arxiv 2024.

67. MagicPIG: LSH Sampling for Efficient LLM Generation. Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, Yang Zhou, Jianyu Zhang, Niklas Nolte, Yuandong Tian, Matthijs Douze, Leon Bottou, Zhihao Jia, Beidi Chen. Arxiv 2024.

68. Not All Heads Matter: A Head-Level KV Cache Compression Method with Integrated Retrieval and Reasoning. Yu Fu, Zefan Cai, Abedelkadir Asi, Wayne Xiong, Yue Dong, Wen Xiao. Arxiv 2024.

69. Long Sequence Modeling with Attention Tensorization: From Sequence to Tensor Learning. Aosong Feng, Rex Ying, Leandros Tassiulas. Arxiv 2024.

70. ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference. Hanshi Sun, Li-Wen Chang, Wenlei Bao, Size Zheng, Ningxin Zheng, Xin Liu, Harry Dong, Yuejie Chi, Beidi Chen. Arxiv 2024.

71. BUZZ: Beehive-structured Sparse KV Cache with Segmented Heavy Hitters for Efficient LLM Inference. Junqi Zhao, Zhijin Fang, Shu Li, Shaohui Yang, Shichao He. Arxiv 2024.

72. VL-Cache: Sparsity and Modality-Aware KV Cache Compression for Vision-Language Model Inference Acceleration. Dezhan Tu, Danylo Vashchilenko, Yuzhe Lu, Panpan Xu. Arxiv 2024.

73. TokenSelect: Efficient Long-Context Inference and Length Extrapolation for LLMs via Dynamic Token-Level KV Cache Selection. Wei Wu, Zhuoshi Pan, Chao Wang, Liyi Chen, Yunchu Bai, Kun Fu, Zheng Wang, Hui Xiong. Arxiv 2024.

74. Recycled Attention: Efficient inference for long-context language models. Fangyuan Xu, Tanya Goyal, Eunsol Choi. Arxiv 2024.

75. Squeezed Attention: Accelerating Long Context Length LLM Inference. Coleman Hooper, Sehoon Kim, Hiva Mohammadzadeh, Monishwaran Maheswaran, June Paik, Michael W. Mahoney, Kurt Keutzer, Amir Gholami. Arxiv 2024.

76. When Precision Meets Position: BFloat16 Breaks Down RoPE in Long-Context Training. Haonan Wang, Qian Liu, Chao Du, Tongyao Zhu, Cunxiao Du, Kenji Kawaguchi, Tianyu Pang. Arxiv 2024.

77. Star Attention: Efficient LLM Inference over Long Sequences. Shantanu Acharya, Fei Jia, Boris Ginsburg. Arxiv 2024.

78. Pushing the Limits of LLM Inference via 2-Bit Layer-Discriminative KV Cache. Akshat Sharma, Hangliang Ding, Jianping Li, Neel Dani, Minjia Zhang. Arxiv 2024.

79. Dynamic-LLaVA: Efficient Multimodal Large Language Models via Dynamic Vision-language Context Sparsification. Wenxuan Huang, Zijie Zhai, Yunhang Shen, Shaoshen Cao, Fei Zhao, Xiangfeng Xu, Zheyu Ye, Shaohui Lin. Arxiv 2024.

80. Compressing KV Cache for Long-Context LLM Inference with Inter-Layer Attention Similarity. Da Ma, Lu Chen, Situo Zhang, Yuxun Miao, Su Zhu, Zhi Chen, Hongshen Xu, Hanqi Li, Shuai Fan, Lei Pan, Kai Yu. Arxiv 2024.

81. AIM: Adaptive Inference of Multi-Modal LLMs via Token Merging and Pruning. Yiwu Zhong, Zhuoming Liu, Yin Li, Liwei Wang. Arxiv 2024.

82. ClusterKV: Manipulating LLM KV Cache in Semantic Space for Recallable Compression. Guangda Liu, Chengwei Li, Jieru Zhao, Chenqi Zhang, Minyi Guo. Arxiv 2024.

83. BatchLLM: Optimizing Large Batched LLM Inference with Global Prefix Sharing and Throughput-oriented Token Batching. Zhen Zheng, Xin Ji, Taosong Fang, Fanghao Zhou, Chuanjie Liu, Gang Peng. Arxiv 2024.

84. Cross-Self KV Cache Pruning for Efficient Vision-Language Inference. Xiaohuan Pei, Tao Huang, Chang Xu. Arxiv 2024.

85. Ltri-LLM: Streaming Long Context Inference for LLMs with Training-Free Dynamic Triangular Attention Pattern. Hongyin Tang, Di Xiu, Lanrui Wang, Xiurui Geng, Jingang Wang, Xunliang Cai. Arxiv 2024.

86. XKV: Personalized KV Cache Memory Reduction for Long-Context LLM Inference. Weizhuo Li, Zhigang Wang, Yu Gu, Ge Yu. Arxiv 2024.

87. SparseAccelerate: Efficient Long-Context Inference for Mid-Range GPUs. James Vo. Arxiv 2024.

88. EMS: Adaptive Evict-then-Merge Strategy for Head-wise KV Cache Compression Based on Global-Local Importance. Yingxin Li, Ye Li, Yuan Meng, Xinzhu Ma, Zihan Geng, Shutao Xia, Zhi Wang. Arxiv 2024.

89. ZigZagkv: Dynamic KV Cache Compression for Long-context Modeling based on Layer Uncertainty. Meizhi Zhong, Xikai Liu, Chen Zhang, Yikun Lei, Yan Gao, Yao Hu, Kehai Chen, Min Zhang. Arxiv 2024.

90. SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator. Guoxuan Chen, Han Shi, Jiawei Li, Yihang Gao, Xiaozhe Ren, Yimeng Chen, Xin Jiang, Zhenguo Li, Weiyang Liu, Chao Huang. Arxiv 2024.

91. More Tokens, Lower Precision: Towards the Optimal Token-Precision Trade-off in KV Cache Compression. Jiebin Zhang, Dawei Zhu, Yifan Song, Wenhao Wu, Chuqiao Kuang, Xiaoguang Li, Lifeng Shang, Qun Liu, Sujian Li. Arxiv 2024.

92. Boosting Long-Context Information Seeking via Query-Guided Activation Refilling. Hongjin Qian, Zheng Liu, Peitian Zhang, Zhicheng Dou, Defu Lian. Arxiv 2024.

93. SCOPE: Optimizing Key-Value Cache Compression in Long-context Generation. Jialong Wu, Zhenglin Wang, Linhai Zhang, Yilong Lai, Yulan He, Deyu Zhou. Arxiv 2024.

94. DynamicKV: Task-Aware Adaptive KV Cache Compression for Long Context LLMs. Xiabin Zhou, Wenbin Wang, Minyan Zeng, Jiaxian Guo, Xuebo Liu, Li Shen, Min Zhang, Liang Ding. Arxiv 2024.

95. HashEvict: A Pre-Attention KV Cache Eviction Strategy using Locality-Sensitive Hashing. Minghui Liu, Tahseen Rabbani, Tony O'Halloran, Ananth Sankaralingam, Mary-Anne Hartley, Brian Gravelle, Furong Huang, Cornelia Fermüller, Yiannis Aloimonos. Arxiv 2024.

96. AdaSkip: Adaptive Sublayer Skipping for Accelerating Long-Context LLM Inference. Zhuomin He, Yizhen Yao, Pengfei Zuo, Bin Gao, Qinya Li, Zhenzhe Zheng, Fan Wu. AAAI 2025.

97. TreeKV: Smooth Key-Value Cache Compression with Tree Structures. Ziwei He, Jian Yuan, Haoli Bai, Jingwen Leng, Bo Jiang. Arxiv 2025.

98. Dynamic Memory Compression: Retrofitting LLMs for Accelerated Inference. Piotr Nawrot, Adrian Łańcucki, Marcin Chochowski, David Tarjan, Edoardo M. Ponti. Arxiv 2024.

99. DeepSeek-V3 Technical Report. DeepSeek-AI, Aixin Liu, Bei Feng, Bing Xue, Bingxuan Wang, Bochao Wu, Chengda Lu, Chenggang Zhao, Chengqi Deng, Chenyu Zhang, Chong Ruan, Damai Dai, Daya Guo, Dejian Yang, Deli Chen, Dongjie Ji, Erhang Li, Fangyun Lin, Fucong Dai, Fuli Luo, Guangbo Hao, Guanting Chen, Guowei Li, H. Zhang, Han Bao, Hanwei Xu, Haocheng Wang, Haowei Zhang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Li, Hui Qu, J.L. Cai, Jian Liang, Jianzhong Guo, Jiaqi Ni, Jiashi Li, Jiawei Wang, Jin Chen, Jingchang Chen, Jingyang Yuan, Junjie Qiu, Junlong Li, Junxiao Song, Kai Dong, Kai Hu, Kaige Gao, Kang Guan, Kexin Huang, Kuai Yu, Lean Wang, Lecong Zhang, Lei Xu, Leyi Xia, Liang Zhao, Litong Wang, Liyue Zhang, Meng Li, Miaojun Wang, Mingchuan Zhang, Minghua Zhang, Minghui Tang, Mingming Li, Ning Tian, Panpan Huang, Peiyi Wang, Peng Zhang, Qiancheng Wang, Qihao Zhu, Qinyu Chen, Qiushi Du, R.J. Chen, R.L. Jin, Ruiqi Ge, Ruisong Zhang, Ruizhe Pan, Runji Wang, Runxin Xu, Ruoyu Zhang, Ruyi Chen, S.S. Li, Shanghao Lu, Shangyan Zhou, Shanhuang Chen, Shaoqing Wu, Shengfeng Ye, Shengfeng Ye, Shirong Ma, Shiyu Wang, Shuang Zhou, Shuiping Yu, Shunfeng Zhou, Shuting Pan, T. Wang, Tao Yun, Tian Pei, Tianyu Sun, W.L. Xiao, Wangding Zeng et al. (100 additional authors not shown). Arxiv 2025.

100. Tensor Product Attention Is All You Need. Yifan Zhang, Yifeng Liu, Huizhuo Yuan, Zhen Qin, Yang Yuan, Quanquan Gu, Andrew Chi-Chih Yao. Arxiv 2025.

101. Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models. Zhenghao Lin, Zihao Tang, Xiao Liu, Yeyun Gong, Yi Cheng, Qi Chen, Hang Li, Ying Xin, Ziyue Yang, Kailai Yang, Yu Yan, Xiao Liang, Shuai Lu, Yiming Huang, Zheheng Luo, Lei Qu, Xuan Feng, Yaoxiang Wang, Yuqing Xia, Feiyang Chen, Yuting Jiang, Yasen Hu, Hao Ni, Binyang Li, Guoshuai Zhao, Jui-Hao Chiang, Zhongxin Guo, Chen Lin, Kun Kuang, Wenjie Li, Yelong Shen, Jian Jiao, Peng Cheng, Mao Yang. Arxiv 2025.

102. CAKE: Cascading and Adaptive KV Cache Eviction with Layer Preferences. Ziran Qin, Yuchen Cao, Mingbao Lin, Wen Hu, Shixuan Fan, Ke Cheng, Weiyao Lin, Jianguo Li. ICLR 2025.

103. AKVQ-VL: Attention-Aware KV Cache Adaptive 2-Bit Quantization for Vision-Language Models. Zunhai Su, Wang Shen, Linge Li, Zhe Chen, Hanyu Wei, Huangqi Yu, Kehong Yuan. Arxiv 2025.

104. ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference. Xiang Liu, Zhenheng Tang, Peijie Dong, Zeyu Li, Bo Li, Xuming Hu, Xiaowen Chu. Arxiv 2025.

105. FastKV: KV Cache Compression for Fast Long-Context Processing with Token-Selective Propagation. Dongwon Jo, Jiwon Song, Yulhwa Kim, Jae-Joon Kim. Arxiv 2025.

106. Can LLMs Maintain Fundamental Abilities under KV Cache Compression?. Xiang Liu, Zhenheng Tang, Hong Chen, Peijie Dong, Zeyu Li, Xiuze Zhou, Bo Li, Xuming Hu, Xiaowen Chu. Arxiv 2025.

107. Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation. Jingyu Liu, Beidi Chen, Ce Zhang. Arxiv 2025.

108. Twilight: Adaptive Attention Sparsity with Hierarchical Top-p Pruning. Chaofan Lin, Jiaming Tang, Shuo Yang, Hanshuo Wang, Tian Tang, Boyu Tian, Ion Stoica, Song Han, Mingyu Gao. Arxiv 2025.

109. AttentionPredictor: Temporal Pattern Matters for Efficient LLM Inference. Qingyue Yang, Jie Wang, Xing Li, Zhihai Wang, Chen Chen, Lei Chen, Xianzhi Yu, Wulong Liu, Jianye Hao, Mingxuan Yuan, Bin Li. Arxiv 2025.

110. Identify Critical KV Cache in LLM Inference from an Output Perturbation Perspective. Yuan Feng, Junlin Lv, Yukun Cao, Xike Xie, S Kevin Zhou. Arxiv 2025.

111. KVTuner: Sensitivity-Aware Layer-wise Mixed Precision KV Cache Quantization for Efficient and Nearly Lossless LLM Inference. Xing Li, Zeyu Xing, Yiming Li, Linping Qu, Hui-Ling Zhen, Wulong Liu, Yiwu Yao, Sinno Jialin Pan, Mingxuan Yuan. Arxiv 2025.

112. Exploiting Sparsity for Long Context Inference: Million Token Contexts on Commodity GPUs. Ryan Synk, Monte Hoover, John Kirchenbauer, Neel Jain, Alex Stein, Manli Shu, Josue Melendez Sanchez, Ramani Duraiswami, Tom Goldstein. Arxiv 2025.

113. Online Scheduling for LLM Inference with KV Cache Constraints. Patrick Jaillet, Jiashuo Jiang, Chara Podimata, Zijie Zhou. Arxiv 2025.

114. BalanceKV: KV Cache Compression through Discrepancy Theory. Insu Han, Michael Kapralov, Ekaterina Kochetkova, Kshiteej Sheth, Amir Zandieh. Arxiv 2025.

115. TransMLA: Multi-Head Latent Attention Is All You Need. Fanxu Meng, Zengwei Yao, Muhan Zhang. Arxiv 2025.

116. InfiniteHiP: Extending Language Model Context Up to 3 Million Tokens on a Single GPU. Heejun Lee, Geon Park, Jaduk Suh, Sung Ju Hwang. Arxiv 2025.

117. RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models. Quan Wei, Chung-Yiu Yau, Hoi-To Wai, Yang (Katie)Zhao, Dongyeop Kang, Youngsuk Park, Mingyi Hong. Arxiv 2025.

118. Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention. Jingyang Yuan, Huazuo Gao, Damai Dai, Junyu Luo, Liang Zhao, Zhengyan Zhang, Zhenda Xie, Y. X. Wei, Lean Wang, Zhiping Xiao, Yuqing Wang, Chong Ruan, Ming Zhang, Wenfeng Liang, Wangding Zeng. Arxiv 2025.

119. QuantSpec: Self-Speculative Decoding with Hierarchical Quantized KV Cache. Rishabh Tiwari, Haocheng Xi, Aditya Tomar, Coleman Hooper, Sehoon Kim, Maxwell Horton, Mahyar Najibi, Michael W. Mahoney, Kurt Keutzer, Amir Gholami. Arxiv 2025.

120. APB: Accelerating Distributed Long-Context Inference by Passing Compressed Context Blocks across GPUs. Yuxiang Huang, Mingye Li, Xu Han, Chaojun Xiao, Weilin Zhao, Sun Ao, Hao Zhou, Jie Zhou, Zhiyuan Liu, Maosong Sun. Arxiv 2025.

121. AdaSplash: Adaptive Sparse Flash Attention. Nuno Gonçalves, Marcos Treviso, André F. T. Martins. Arxiv 2025.

122. Tactic: Adaptive Sparse Attention with Clustering and Distribution Fitting for Long-Context LLMs. Kan Zhu, Tian Tang, Qinyu Xu, Yile Gu, Zhichen Zeng, Rohan Kadekodi, Liangyu Zhao, Ang Li, Arvind Krishnamurthy, Baris Kasikci. Arxiv 2025.

123. HeadInfer: Memory-Efficient LLM Inference by Head-wise Offloading. Cheng Luo, Zefan Cai, Hanshi Sun, Jinqi Xiao, Bo Yuan, Wen Xiao, Junjie Hu, Jiawei Zhao, Beidi Chen, Anima Anandkumar. Arxiv 2025.

124. A2ATS: Retrieval-Based KV Cache Reduction via Windowed Rotary Position Embedding and Query-Aware Vector Quantization. Junhui He, Junna Xing, Nan Wang, Rui Xu, Shangyu Wu, Peng Zhou, Qiang Liu, Chun Jason Xue, Qingan Li. Arxiv 2025.

125. BaKlaVa -- Budgeted Allocation of KV cache for Long-context Inference. Ahmed Burak Gulhan, Krishna Teja Chitty-Venkata, Murali Emani, Mahmut Kandemir, Venkatram Vishwanath. Arxiv 2025.

126. Activation-aware Probe-Query: Effective Key-Value Retrieval for Long-Context LLMs Inference. Qingfa Xiao, Jiachuan Wang, Haoyang Li, Cheng Deng, Jiaqi Tang, Shuangyin Li, Yongqi Zhang, Jun Wang, Lei Chen. Arxiv 2025.

127. RocketKV: Accelerating Long-Context LLM Inference via Two-Stage KV Cache Compression. Payman Behnam, Yaosheng Fu, Ritchie Zhao, Po-An Tsai, Zhiding Yu, Alexey Tumanov. Arxiv 2025.

128. LServe: Efficient Long-sequence LLM Serving with Unified Sparse Attention. Shang Yang, Junxian Guo, Haotian Tang, Qinghao Hu, Guangxuan Xiao, Jiaming Tang, Yujun Lin, Zhijian Liu, Yao Lu, Song Han. MLSys 2025.

129. Unshackling Context Length: An Efficient Selective Attention Approach through Query-Key Compression. Haoyu Wang, Tong Teng, Tianyu Guo, An Xiao, Duyu Tang, Hanting Chen, Yunhe Wang. Arxiv 2025.

130. Towards Economical Inference: Enabling DeepSeek's Multi-Head Latent Attention in Any Transformer-based LLMs. Tao Ji, Bin Guo, Yuanbin Wu, Qipeng Guo, Lixing Shen, Zhan Chen, Xipeng Qiu, Qi Zhang, Tao Gui. Arxiv 2025.

131. SVDq: 1.25-bit and 410x Key Cache Compression for LLM Attention. Hong Yankun, Li Xing, Zhen Hui-Ling, Yu Xianzhi, Liu Wulong, Yuan Mingxuan. Arxiv 2025.

132. Round Attention: A Novel Round-Level Attention Mechanism to Accelerate LLM Inference. Yaohua Tang, Zhicheng Hu, Kun Cheng, Fan Mo, Qiheng Lv, Hua Wang, Zhi Chen. Arxiv 2025.

133. DBudgetKV: Dynamic Budget in KV Cache Compression for Ensuring Optimal Performance. Xuanfan Ni, Liyan Xu, Chenyang Lyu, Longyue Wang, Mo Yu, Lemao Liu, Fandong Meng, Jie Zhou, Piji Li. Arxiv 2025.

134. KVLink: Accelerating Large Language Models via Efficient KV Cache Reuse. Jingbo Yang, Bairu Hou, Wei Wei, Yujia Bao, Shiyu Changi. Arxiv 2025.

135. FairKV: Balancing Per-Head KV Cache for Fast Multi-GPU Inference. Bingzhe Zhao, Ke Cheng, Aomufei Yuan, Yuxuan Tian, Ruiguang Zhong, Chengchen Hu, Tong Yang, Lian Yu. Arxiv 2025.

136. CoKV: Optimizing KV Cache Allocation via Cooperative Game. Qiheng Sun, Hongwei Zhang, Haocheng Xia, Jiayao Zhang, Jinfei Liu, Kui Ren. Arxiv 2025.

137. MEDA: Dynamic KV Cache Allocation for Efficient Multimodal Long-Context Inference. Zhongwei Wan, Hui Shen, Xin Wang, Che Liu, Zheda Mai, Mi Zhang. NAACL 2025.

138. FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference. Xunhao Lai, Jianqiao Lu, Yao Luo, Yiyuan Ma, Xun Zhou. ICLR 2025 Oral.

139. WeightedKV: Attention Scores Weighted Key-Value Cache Merging for Large Language Models. Jian Yuan, Ziwei He, Haoli Bai, Jingwen Leng, Bo Jiang. ICASSP 2025.

140. Dialogue Without Limits: Constant-Sized KV Caches for Extended Responses in LLMs. Ravi Ghadia, Avinash Kumar, Gaurav Jain, Prashant Nair, Poulami Das. Arxiv 2025.

141. KVCrush: Key value cache size-reduction using similarity in head-behaviour. Gopi Krishna Jha, Sameh Gobriel, Liubov Talamanova, Alexander Kozlov, Nilesh Jain. Arxiv 2025.

142. EliteKV: Scalable KV Cache Compression via RoPE Frequency Selection and Joint Low-Rank Projection. Yuhao Zhou, Sirui Song, Boyang Liu, Zhiheng Xi, Senjie Jin, Xiaoran Fan, Zhihao Zhang, Wei Li, Xuanjing Huang. Arxiv 2025.

143. Progressive Sparse Attention: Algorithm and System Co-design for Efficient Attention in LLM Serving. Qihui Zhou, Peiqi Yin, Pengfei Zuo, James Cheng. Arxiv 2025.

144. Q-Filters: Leveraging QK Geometry for Efficient KV Cache Compression. Nathan Godey, Alessio Devoto, Yu Zhao, Simone Scardapane, Pasquale Minervini, Éric de la Clergerie, Benoît Sagot. Arxiv 2025.

145. TokenButler: Token Importance is Predictable. Yash Akhauri, Ahmed F AbouElhamayed, Yifei Gao, Chi-Chih Chang, Nilesh Jain, Mohamed S. Abdelfattah. Arxiv 2025.

146. Slim attention: cut your context memory in half without loss of accuracy -- K-cache is all you need for MHA. Nils Graef, Andrew Wasielewski. Arxiv 2025.

147. LLMs Know What to Drop: Self-Attention Guided KV Cache Eviction for Efficient Long-Context Inference. Guangtao Wang, Shubhangi Upasani, Chen Wu, Darshan Gandhi, Jonathan Li, Changran Hu, Bo Li, Urmish Thakker. ICLR 2025.

148. KV-Distill: Nearly Lossless Learnable Context Compression for LLMs. Vivek Chari, Guanghui Qin, Benjamin Van Durme. Arxiv 2025.

149. Radar: Fast Long-Context Decoding for Any Transformer. Yongchang Hao, Mengyao Zhai, Hossein Hajimirsadeghi, Sepidehsadat Hosseini, Frederick Tung. ICLR 2025.

150. ZeroMerge: Parameter-Free KV Cache Compression for Memory-Efficient Long-Context LLMs. Xin Liu, Pei Liu, Guoming Tang. Arxiv 2025.

151. Exploring the Limits of KV Cache Compression in Visual Autoregressive Transformers. Bo Chen, Xiaoyu Li, Yekun Ke, Yingyu Liang, Zhenmei Shi, Zhao Song. Arxiv 2025.

152. SpeCache: Speculative Key-Value Caching for Efficient Generation of LLMs. Shibo Jie, Yehui Tang, Kai Han, Zhi-Hong Deng, Jing Han. Arxiv 2025.

153. KVShare: Semantic-Aware Key-Value Cache Sharing for Efficient Large Language Model Inference. Huan Yang, Renji Zhang, Deyu Zhang. Arxiv 2025.

154. xKV: Cross-Layer SVD for KV-Cache Compression. Chi-Chih Chang, Chien-Yu Lin, Yash Akhauri, Wei-Cheng Lin, Kai-Chiang Wu, Luis Ceze, Mohamed S. Abdelfattah. Arxiv 2025.

155. WindowKV: Task-Adaptive Group-Wise KV Cache Window Selection for Efficient LLM Inference. Youhui Zuo, Sibo Wei, Chen Zhang, Zhuorui Liu, Wenpeng Lu, Dawei Song. Arxiv 2025.

156. BitDecoding: Unlocking Tensor Cores for Long-Context LLMs Decoding with Low-Bit KV Cache. Dayou Du, Shijie Cao, Jianyi Cheng, Ting Cao, Mao Yang. Arxiv 2025.

157. Oaken: Fast and Efficient LLM Serving with Online-Offline Hybrid KV Cache Quantization. Minsu Kim, Seongmin Hong, RyeoWook Ko, Soongyu Choi, Hunjong Lee, Junsoo Kim, Joo-Young Kim, Jongse Park. Arxiv 2025.

158. LogQuant: Log-Distributed 2-Bit Quantization of KV Cache with Superior Accuracy Preservation. Han Chen, Zicong Jiang, Zining Zhang, Bingsheng He, Pingyi Luo, Mian Lu, Yuqiang Chen. ICLR 2025.

159. Cocktail: Chunk-Adaptive Mixed-Precision Quantization for Long-Context LLM Inference. Wei Tao, Bin Zhang, Xiaoyang Qu, Jiguang Wan, Jianzong Wang. DATE 2025.

160. PromptDistill: Query-based Selective Token Retention in Intermediate Layers for Efficient Large Language Model Inference. Weisheng Jin, Maojia Song, Tej Deep Pala, Yew Ken Chia, Amir Zadeh, Chuan Li, Soujanya Poria. Arxiv 2025.

161. SQuat: Subspace-orthogonal KV Cache Quantization. Hao Wang, Ligong Han, Kai Xu, Akash Srivastava. Arxiv 2025.

162. Rethinking Key-Value Cache Compression Techniques for Large Language Model Serving. Wei Gao, Xinyu Zhou, Peng Sun, Tianwei Zhang, Yonggang Wen. MLSys 2025.

163. SentenceKV: Efficient LLM Inference via Sentence-Level Semantic KV Caching. Yuxuan Zhu, Ali Falahati, David H. Yang, Mohammad Mohammadi Amiri. Arxiv 2025.

164. LagKV: Lag-Relative Information of the KV Cache Tells Which Tokens Are Important. Manlai Liang, JiaMing Zhang, Xiong Li, Jinlong Li. Arxiv 2025.

165. FlowKV: A Disaggregated Inference Framework with Low-Latency KV Cache Transfer and Load-Aware Scheduling. Weiqing Li, Guochao Jiang, Xiangyong Ding, Zhangcheng Tao, Chuzhan Hao, Chenfeng Xu, Yuewei Zhang, Hao Wang. Arxiv 2025.

166. Apt-Serve: Adaptive Request Scheduling on Hybrid Cache for Scalable LLM Inference Serving. Shihong Gao, Xin Zhang, Yanyan Shen, Lei Chen. Arxiv 2025.

167. KeepKV: Eliminating Output Perturbation in KV Cache Compression for Efficient LLMs Inference. Yuxuan Tian, Zihan Wang, Yebo Peng, Aomufei Yuan, Zhiming Wang, Bairen Yi, Xin Liu, Yong Cui, Tong Yang. Arxiv 2025.

168. MOM: Memory-Efficient Offloaded Mini-Sequence Inference for Long Context Language Models. Junyang Zhang, Tianyi Zhu, Cheng Luo, Anima Anandkumar. Arxiv 2025.

169. CAOTE: KV Caching through Attention Output Error based Token Eviction. Raghavv Goel, Junyoung Park, Mukul Gagrani, Dalton Jones, Matthew Morse, Harper Langston, Mingu Lee, Chris Lott. Arxiv 2025.

170. SlimPipe: Memory-Thrifty and Efficient Pipeline Parallelism for Long-Context LLM Training. Zhouyang Li, Yuliang Liu, Wei Zhang, Tailing Yuan, Bin Chen, Chengru Song, Di Zhang. Arxiv 2025.

171. FreqKV: Frequency Domain Key-Value Compression for Efficient Context Window Extension. Jushi Kai, Boyi Zeng, Yixuan Wang, Haoli Bai, Bo Jiang, Zhouhan Lin. Arxiv 2025.

172. dKV-Cache: The Cache for Diffusion Language Models. Xinyin Ma, Runpeng Yu, Gongfan Fang, Xinchao Wang. Arxiv 2025.

173. PM-KVQ: Progressive Mixed-precision KV Cache Quantization for Long-CoT LLMs. Tengxuan Liu, Shiyao Li, Jiayi Yang, Tianchen Zhao, Feng Zhou, Xiaohui Song, Guohao Dai, Shengen Yan, Huazhong Yang, Yu Wang. Arxiv 2025.

174. TailorKV: A Hybrid Framework for Long-Context Inference via Tailored KV Cache Optimization. Dingyu Yao, Bowen Shen, Zheng Lin, Wei Liu, Jian Luan, Bin Wang, Weiping Wang. Arxiv 2025.

175. R-KV: Redundancy-aware KV Cache Compression for Training-Free Reasoning Models Acceleration. Zefan Cai, Wen Xiao, Hanshi Sun, Cheng Luo, Yikai Zhang, Ke Wan, Yucheng Li, Yeyang Zhou, Li-Wen Chang, Jiuxiang Gu, Zhen Dong, Anima Anandkumar, Abedelkadir Asi, Junjie Hu. Arxiv 2025.

176. ReCalKV: Low-Rank KV Cache Compression via Head Reordering and Offline Calibration. Xianglong Yan, Zhiteng Li, Tianao Zhang, Linghe Kong, Yulun Zhang, Xiaokang Yang. Arxiv 2025.

177. VScan: Rethinking Visual Token Reduction for Efficient Large Vision-Language Models. Ce Zhang, Kaixin Ma, Tianqing Fang, Wenhao Yu, Hongming Zhang, Zhisong Zhang, Yaqi Xie, Katia Sycara, Haitao Mi, Dong Yu. Arxiv 2025.

178. KVzip: Query-Agnostic KV Cache Compression with Context Reconstruction. Jang-Hyun Kim, Jinuk Kim, Sangwoo Kwon, Jae W. Lee, Sangdoo Yun, Hyun Oh Song. Arxiv 2025.

179. Mustafar: Promoting Unstructured Sparsity for KV Cache Pruning in LLM Inference. Donghyeon Joo, Helya Hosseini, Ramyad Hadidi, Bahar Asgari. Arxiv 2025.

180. Lookahead Q-Cache: Achieving More Consistent KV Cache Eviction via Pseudo Query. Yixuan Wang, Shiyu Ji, Yijun Liu, Yuzhuang Xu, Yang Xu, Qingfu Zhu, Wanxiang Che. Arxiv 2025.

181. Hardware-Efficient Attention for Fast Decoding. Ted Zadouri, Hubert Strauss, Tri Dao. Arxiv 2025.

182. Accelerating Diffusion Language Model Inference via Efficient KV Caching and Guided Diffusion. Zhanqiu Hu, Jian Meng, Yash Akhauri, Mohamed S. Abdelfattah, Jae-sun Seo, Zhiru Zhang, Udit Gupta. Arxiv 2025.

183. AhaKV: Adaptive Holistic Attention-Driven KV Cache Eviction for Efficient Inference of Large Language Models. Yifeng Gu, Zicong Jiang, Jianxiu Jin, Kailing Guo, Ziyang Zhang, Xiangmin Xu. Arxiv 2025.

184. Inference-Time Hyper-Scaling with KV Cache Compression. Adrian Łańcucki, Konrad Staniszewski, Piotr Nawrot, Edoardo M. Ponti. Arxiv 2025.

185. TaDA: Training-free recipe for Decoding with Adaptive KV Cache Compression and Mean-centering. Vinay Joshi, Pratik Prabhanjan Brahma, Zicheng Liu, Emad Barsoum. Arxiv 2025.

186. Homogeneous Keys, Heterogeneous Values: Exploiting Local KV Cache Asymmetry for Long-Context LLMs. Wanyun Cui, Mingwei Xu. Arxiv 2025.

187. Paged Attention Meets FlexAttention: Unlocking Long-Context Efficiency in Deployed Inference. Thomas Joshi, Herman Saini, Neil Dhillon, Antoni Viros i Martin, Kaoutar El Maghraoui. Arxiv 2025.

188. KVmix: Gradient-Based Layer Importance-Aware Mixed-Precision Quantization for KV Cache. Fei Li, Song Liu, Weiguo Wu, Shiqiang Nie, Jinyu Wang. Arxiv 2025.

189. Efficient Long-Context LLM Inference via KV Cache Clustering. Jie Hu, Shengnan Wang, Yutong He, Ping Gong, Jiawei Yi, Juncheng Zhang, Youhui Bai, Renhai Chen, Gong Zhang, Cheng Li, Kun Yuan. Arxiv 2025.

190. Beyond Homogeneous Attention: Memory-Efficient LLMs via Fourier-Approximated KV Cache. Xiaoran Liu, Siyang He, Qiqi Wang, Ruixiao Li, Yuerong Song, Zhigeng Liu, Linlin Li, Qun Liu, Zengfeng Huang, Qipeng Guo, Ziwei He, Xipeng Qiu. Arxiv 2025.

191. Latent Multi-Head Attention for Small Language Models. Sushant Mehta, Raj Dandekar, Rajat Dandekar, Sreedath Panat. Arxiv 2025.

192. Multipole Attention for Efficient Long Context Reasoning. Coleman Hooper, Sebastian Zhao, Luca Manolache, Sehoon Kim, Michael W. Mahoney, Yakun Sophia Shao, Kurt Keutzer, Amir Gholami. Arxiv 2025.

193. Mixture of Weight-shared Heterogeneous Group Attention Experts for Dynamic Token-wise KV Optimization. Guanghui Song, Dongping Liao, Yiren Zhao, Kejiang Ye, Cheng-zhong Xu, Xitong Gao. Arxiv 2025.

194. Cache Me If You Can: How Many KVs Do You Need for Effective Long-Context LMs?. Adithya Bhaskar, Alexander Wettig, Tianyu Gao, Yihe Dong, Danqi Chen. Arxiv 2025.

195. LazyEviction: Lagged KV Eviction with Attention Pattern Observation for Efficient Long Reasoning. Haoyue Zhang, Hualei Zhang, Xiaosong Ma, Jie Zhang, Song Guo. Arxiv 2025.

196. CommVQ: Commutative Vector Quantization for KV Cache Compression. Junyan Li, Yang Zhang, Muhammad Yusuf Hassan, Talha Chafekar, Tianle Cai, Zhile Ren, Pengsheng Guo, Foroozan Karimzadeh, Colorado Reed, Chong Wang, Chuang Gan. Arxiv 2025.

197. SpindleKV: A Novel KV Cache Reduction Method Balancing Both Shallow and Deep Layers. Zicong Tang, Shi Luohe, Zuchao Li, Baoyuan Qi, Guoming Liu, Lefei Zhang, Ping Wang. ACL 2025.

198. Krul: Efficient State Restoration for Multi-turn Conversations with Dynamic Cross-layer KV Sharing. Junyi Wen, Junyuan Liang, Zicong Hong, Wuhui Chen, Zibin Zheng. Arxiv 2025.

199. Compactor: Calibrated Query-Agnostic KV Cache Compression with Approximate Leverage Scores. Vivek Chari, Benjamin Van Durme. Arxiv 2025.

200. Think Clearly: Improving Reasoning via Redundant Token Pruning. Daewon Choi, Jimin Lee, Jihoon Tack, Woomin Song, Saket Dingliwal, Sai Muralidhar Jayanthi, Bhavana Ganesh, Jinwoo Shin, Aram Galstyan, Sravan Babu Bodapati. Arxiv 2025.

201. AlayaDB: The Data Foundation for Efficient and Effective Long-context LLM Inference Yangshen Deng, Zhengxin You, Long Xiang, Qilong Li, Peiqi Yuan, Zhaoyang Hong, Yitao Zheng, Wanting Li, Runzhong Li, Haotian Liu, Kyriakos Mouratidis, Man Lung Yiu, Huan Li, Qiaomu Shen, Rui Mao, Bo Tang. SIGMOD 2025.

202. LoopServe: An Adaptive Dual-phase LLM Inference Acceleration System for Multi-Turn Dialogues. Haoyang Li, Zhanchao Xu, Yiming Li, Xuejia Chen, Darian Li, Anxin Tian, Qingfa Xiao, Cheng Deng, Jun Wang, Qing Li, Lei Chen, Mingxuan Yuan. Arxiv 2025.

203. LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models. Dachuan Shi, Yonggan Fu, Xiangchi Yuan, Zhongzhi Yu, Haoran You, Sixu Li, Xin Dong, Jan Kautz, Pavlo Molchanov, Yingyan (Celine)Lin. ICML 2025.

204. CaliDrop: KV Cache Compression with Calibration. Yi Su, Quantong Qiu, Yuechi Zhou, Juntao Li, Qingrong Xia, Ping Li, Xinyu Duan, Zhefeng Wang, Min Zhang. Arxiv 2025.

205. HCAttention: Extreme KV Cache Compression via Heterogeneous Attention Computing for LLMs. Dongquan Yang, Yifan Yang, Xiaotian Yu, Xianbiao Qi, Rong Xiao. Arxiv 2025.

206. FAEDKV: Infinite-Window Fourier Transform for Unbiased KV Cache Compression. Runchao Li, Yao Fu, Mu Sheng, Xianxuan Long, Haotian Yu, Pan Li. Arxiv 2025.

207. CompressKV: Semantic Retrieval Heads Know What Tokens are Not Important Before Generation. Xiaolin Lin, Jingcun Wang, Olga Kondrateva, Yiyu Shi, Bing Li, Grace Li Zhang. Arxiv 2025.

208. LeanK: Learnable K Cache Channel Pruning for Efficient Decoding. Yike Zhang, Zhiyuan He, Huiqiang Jiang, Chengruidong Zhang, Yuqing Yang, Jianyong Wang, Lili Qiu. Arxiv 2025.

209. KVSink: Understanding and Enhancing the Preservation of Attention Sinks in KV Cache Quantization for LLMs. Zunhai Su, Kehong Yuan. COLM 2025.

210. SlimInfer: Accelerating Long-Context LLM Inference via Dynamic Token Pruning. Lingkun Long, Rubing Yang, Yushi Huang, Desheng Hui, Ao Zhou, Jianlei Yang. Arxiv 2025.

211. Retrospective Sparse Attention for Efficient Long-Context Generation. Seonghwan Choi, Beomseok Kang, Dongwon Jo, Jae-Joon Kim. Arxiv 2025.

212. XQuant: Breaking the Memory Wall for LLM Inference with KV Cache Rematerialization. Aditya Tomar, Coleman Hooper, Minjae Lee, Haocheng Xi, Rishabh Tiwari, Wonjun Kang, Luca Manolache, Michael W. Mahoney, Kurt Keutzer, Amir Gholami. Arxiv 2025.

213. Sparse Attention across Multiple-context KV Cache. Ziyi Cao, Qingyi Si, Jingbin Zhang, Bingquan Liu. Arxiv 2025.

214. SparK: Query-Aware Unstructured Sparsity with Recoverable KV Cache Channel Pruning. Huanxuan Liao, Yixing Xu, Shizhu He, Guanchen Li, Xuanwu Yin, Dong Li, Emad Barsoum, Jun Zhao, Kang Liu. Arxiv 2025.

215. Spotlight Attention: Towards Efficient LLM Generation via Non-linear Hashing-based KV Cache Retrieval. Wenhao Li, Yuxin Zhang, Gen Luo, Haiyuan Wan, Ziyang Gong, Fei Chao, Rongrong Ji. Arxiv 2025.

216. GraphKV: Breaking the Static Selection Paradigm with Graph-Based KV Cache Eviction. Xuelin Li, Xiangqi Jin, Linfeng Zhang. Arxiv 2025.

217. KVCompose: Efficient Structured KV Cache Compression with Composite Tokens. Dmitry Akulov, Mohamed Sana, Antonio De Domenico, Tareq Si Salem, Nicola Piovesan, Fadhel Ayed. Arxiv 2025.

218. EvolKV: Evolutionary KV Cache Compression for LLM Inference. Bohan Yu, Yekun Chai. Arxiv 2025.

219. LAVa: Layer-wise KV Cache Eviction with Dynamic Budget Allocation. Yiqun Shen, Song Yuan, Zhengze Zhang, Xiaoliang Wang, Daxin Jiang, Nguyen Cam-Tu. Arxiv 2025.

220. UniGist: Towards General and Hardware-aligned Sequence-level Long Context Compression. Chenlong Deng, Zhisong Zhang, Kelong Mao, Shuaiyi Li, Tianqing Fang, Hongming Zhang, Haitao Mi, Dong Yu, Zhicheng Dou. Arxiv 2025.

221. EpiCache: Episodic KV Cache Management for Long Conversational Question Answering. Minsoo Kim, Arnav Kundu, Hana_Byul Kim, Richa Dixit, Minsik Cho. Arxiv 2025.

222. OjaKV: Context-Aware Online Low-Rank KV Cache Compression with Oja's Rule. Yuxuan Zhu, David H. Yang, Mohammad Mohammadi Amiri, Keerthiram Murugesan, Tejaswini Pedapati, Pin-Yu Chen. Arxiv 2025.

223. ProxyAttn: Guided Sparse Attention via Representative Heads. Yixuan Wang, Huang He, Siqi Bao, Hua Wu, Haifeng Wang, Qingfu Zhu, Wanxiang Che. Arxiv 2025.

224. StreamKV: Streaming Video Question-Answering with Segment-based KV Cache Retrieval and Compression. Yilong Chen, Xiang Bai, Zhibin Wang, Chengyu Bai, Yuhan Dai, Ming Lu, Shanghang Zhang. Arxiv 2025.

225. VLA-Pruner: Temporal-Aware Dual-Level Visual Token Pruning for Efficient Vision-Language-Action Inference. Ziyan Liu, Yeqiu Chen, Hongyi Cai, Tao Lin, Shuo Yang, Zheng Liu, Bo Zhao. Arxiv 2025.

226. Revisiting Multimodal KV Cache Compression: A Frequency-Domain-Guided Outlier-KV-Aware Approach. Yaoxin Yang, Peng Ye, Xudong Tan, Chongjun Tu, Maosen Zhao, Jia Hao, Tao Chen. Arxiv 2025.

227. Frequency-Aware Token Reduction for Efficient Vision Transformer. Dong-Jae Lee, Jiwan Hur, Jaehyun Choi, Jaemyung Yu, Junmo Kim. NeurIPS 2025.

3. Recurrent Transformers

1. Transformer-XL: Attentive language models beyond a fixed-length context. Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc V. Le, Ruslan Salakhutdinov. ACL 2019.

2. Compressive Transformers for Long-Range Sequence Modelling. Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, Timothy P. Lillicrap. Arxiv 2019.

3. Memformer: The memory-augmented transformer. Qingyang Wu, Zhenzhong Lan, Kun Qian, Jing Gu, Alborz Geramifard, Zhou Yu. Arxiv 2020.

4. ERNIE-Doc: A Retrospective Long-Document Modeling Transformer. SiYu Ding, Junyuan Shang, Shuohuan Wang, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang. ACL-IJCNLP 2021.

5. Memorizing Transformers. Yuhuai Wu, Markus N. Rabe, DeLesley Hutchins, Christian Szegedy. Arxiv 2022.

6. Recurrent Attention Networks for Long-text Modeling. Xianming Li, Zongxi Li, Xiaotian Luo, Haoran Xie, Xing Lee, Yingbin Zhao, Fu Lee Wang, Qing Li. ACL 2023.

7. RWKV: Reinventing RNNs for the Transformer Era. Bo Peng, Eric Alcaide, Quentin Anthony, Alon Albalak, Samuel Arcadinho, Huanqi Cao, Xin Cheng, Michael Chung, Matteo Grella, Kranthi Kiran GV, Xuzheng He, Haowen Hou, Przemyslaw Kazienko, Jan Kocon, Jiaming Kong, Bartlomiej Koptyra, Hayden Lau, Krishna Sri Ipsit Mantri, Ferdinand Mom, Atsushi Saito, Xiangru Tang, Bolun Wang, Johan S. Wind, Stansilaw Wozniak, Ruichong Zhang, Zhenyuan Zhang, Qihang Zhao, Peng Zhou, Jian Zhu, Rui-Jie Zhu. Arxiv 2023.        

8. Segmented Recurrent Transformer: An Efficient Sequence-to-Sequence Model. Yinghan Long, Sayeed Shafayet Chowdhury, Kaushik Roy. Arxiv 2023.

9. Scaling Transformer to 1M tokens and beyond with RMT. Aydar Bulatov, Yuri Kuratov, Mikhail S. Burtsev. Arxiv 2023.

10. Block-Recurrent Transformers. DeLesley Hutchins, Imanol Schlag, Yuhuai Wu, Ethan Dyer, Behnam Neyshabur. Arxiv 2023.

11. TRAMS: Training-free Memory Selection for Long-range Language Modeling. Haofei Yu, Cunxiang Wang, Yue Zhang, Wei Bi. Arxiv 2023.

12. Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. Soham De, Samuel L. Smith, Anushan Fernando, Aleksandar Botev, George Cristian-Muraru, Albert Gu, Ruba Haroun, Leonard Berrada, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, Arnaud Doucet, David Budden, Yee Whye Teh, Razvan Pascanu, Nando De Freitas, Caglar Gulcehre. Arxiv 2024.

13. Extensible Embedding: A Flexible Multipler For LLM's Context Length. Ninglu Shao, Shitao Xiao, Zheng Liu, Peitian Zhang. Arxiv 2024.

14. Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence. Bo Peng, Daniel Goldstein, Quentin Anthony, Alon Albalak, Eric Alcaide, Stella Biderman, Eugene Cheah, Teddy Ferdinan, Haowen Hou, Przemysław Kazienko, Kranthi Kiran GV, Jan Kocoń, Bartłomiej Koptyra, Satyapriya Krishna, Ronald McClelland Jr., Niklas Muennighoff, Fares Obeid, Atsushi Saito, Guangyu Song, Haoqin Tu, Stanisław Woźniak, Ruichong Zhang, Bingchen Zhao, Qihang Zhao, Peng Zhou, Jian Zhu, Rui-Jie Zhu. Arxiv 2024.                

15. Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention. Tsendsuren Munkhdalai, Manaal Faruqui, Siddharth Gopal. Arxiv 2024.

16. RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. Aleksandar Botev, Soham De, Samuel L Smith, Anushan Fernando, George-Cristian Muraru, Ruba Haroun, Leonard Berrada, Razvan Pascanu, Pier Giuseppe Sessa, Robert Dadashi, Léonard Hussenot, Johan Ferret, Sertan Girgin, Olivier Bachem, Alek Andreev, Kathleen Kenealy, Thomas Mesnard, Cassidy Hardin, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivière, Mihir Sanjay Kale, Juliette Love, Pouya Tafti, Armand Joulin, Noah Fiedel, Evan Senter, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, David Budden, Arnaud Doucet, Sharad Vikram, Adam Paszke, Trevor Gale, Sebastian Borgeaud, Charlie Chen, Andy Brock, Antonia Paterson, Jenny Brennan, Meg Risdal, Raj Gundluru, Nesh Devanathan, Paul Mooney, Nilay Chauhan, Phil Culliton, Luiz GUStavo Martins, Elisa Bandy, David Huntsperger, Glenn Cameron, Arthur Zucker, Tris Warkentin, Ludovic Peran, Minh Giang, Zoubin Ghahramani, Clément Farabet, Koray Kavukcuoglu, Demis Hassabis, Raia Hadsell, Yee Whye Teh, Nando de Frietas. Arxiv 2024.

17. Linearizing Large Language Models. Jean Mercat, Igor Vasiljevic, Sedrick Keh, Kushal Arora, Achal Dave, Adrien Gaidon, Thomas Kollar. Arxiv 2024.

18. VisualRWKV: Exploring Recurrent Neural Networks for Visual Language Models. Haowen Hou, Peigen Zeng, Fei Ma, Fei Richard Yu. Arxiv 2024.

19. Just read twice: closing the recall gap for recurrent language models. Simran Arora, Aman Timalsina, Aaryan Singhal, Benjamin Spector, Sabri Eyuboglu, Xinyi Zhao, Ashish Rao, Atri Rudra, Christopher Ré. Arxiv 2024.

20. Associative Recurrent Memory Transformer. Ivan Rodkin, Yuri Kuratov, Aydar Bulatov, Mikhail Burtsev. ICML 2024 Workshop.

21. GoldFinch: High Performance RWKV/Transformer Hybrid with Linear Pre-Fill and Extreme KV-Cache Compression. Daniel Goldstein, Fares Obeid, Eric Alcaide, Guangyu Song, Eugene Cheah. Arxiv 2024.

22. Analysis of Argument Structure Constructions in a Deep Recurrent Language Model. Pegah Ramezani, Achim Schilling, Patrick Krauss. Arxiv 2024.

23. xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference. Maximilian Beck, Korbinian Pöppel, Phillip Lippe, Richard Kurle, Patrick M. Blies, Günter Klambauer, Sebastian Böck, Sepp Hochreiter. Arxiv 2025.

24. EdgeInfinite: A Memory-Efficient Infinite-Context Transformer for Edge Devices. Jiyu Chen, Shuang Peng, Daxiong Luo, Fan Yang, Renshou Wu, Fangyuan Li, Xiaoxin Chen. ACL 2025.

25. Artificial Hippocampus Networks for Efficient Long-Context Modeling Yunhao Fang, Weihao Yu, Shu Zhong, Qinghao Ye, Xuehan Xiong, Lai Wei. Arxiv 2025.

4. State Space Models

1. Mamba: Linear-Time Sequence Modeling with Selective State Spaces. Albert Gu, Tri Dao. Arxiv 2023.

2. MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts. Maciej Pióro, Kamil Ciebiera, Krystian Król, Jan Ludziejewski, Sebastian Jaszczur. Arxiv 2024.

3. MambaByte: Token-free Selective State Space Model. Junxiong Wang, Tushaar Gangavarapu, Jing Nathan Yan, Alexander M Rush. Arxiv 2024.

4. LOCOST: State-Space Models for Long Document Abstractive Summarization. Florian Le Bronnec, Song Duong, Mathieu Ravaut, Alexandre Allauzen, Nancy F. Chen, Vincent Guigue, Alberto Lumbreras, Laure Soulier, Patrick Gallinari. Arxiv 2024.

5. State Space Models as Foundation Models: A Control Theoretic Overview. Carmen Amo Alonso, Jerome Sieber, Melanie N. Zeilinger. Arxiv 2024.

6. Jamba: A Hybrid Transformer-Mamba Language Model. Opher Lieber, Barak Lenz, Hofit Bata, Gal Cohen, Jhonathan Osin, Itay Dalmedigos, Erez Safahi, Shaked Meirom, Yonatan Belinkov, Shai Shalev-Shwartz, Omri Abend, Raz Alon, Tomer Asida, Amir Bergman, Roman Glozman, Michael Gokhman, Avashalom Manevich, Nir Ratner, Noam Rozen, Erez Shwartz, Mor Zusman, Yoav Shoham. Arxiv 2024.

7. Robustifying State-space Models for Long Sequences via Approximate Diagonalization. Annan Yu, Arnur Nigmetov, Dmitriy Morozov, Michael W. Mahoney, N. Benjamin Erichson. ICLR 2024 Spotlight.

8. Zamba: A Compact 7B SSM Hybrid Model. Paolo Glorioso, Quentin Anthony, Yury Tokpanov, James Whittington, Jonathan Pilault, Adam Ibrahim, Beren Millidge. Arxiv 2024.

9. Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality. Tri Dao, Albert Gu. Arxiv 2024.

10. Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling. Liliang Ren, Yang Liu, Yadong Lu, Yelong Shen, Chen Liang, Weizhu Chen. Arxiv 2024.

11. An Empirical Study of Mamba-based Language Models. Roger Waleffe, Wonmin Byeon, Duncan Riach, Brandon Norick, Vijay Korthikanti, Tri Dao, Albert Gu, Ali Hatamizadeh, Sudhakar Singh, Deepak Narayanan, Garvit Kulshreshtha, Vartika Singh, Jared Casper, Jan Kautz, Mohammad Shoeybi, Bryan Catanzaro. Arxiv 2024.

12. B'MOJO: Hybrid State Space Realizations of Foundation Models with Eidetic and Fading Memory. Luca Zancato, Arjun Seshadri, Yonatan Dukler, Aditya Golatkar, Yantao Shen, Benjamin Bowman, Matthew Trager, Alessandro Achille, Stefano Soatto. Arxiv 2024.

13. MambaForGCN: Enhancing Long-Range Dependency with State Space Model and Kolmogorov-Arnold Networks for Aspect-Based Sentiment Analysis. Adamu Lawan, Juhua Pu, Haruna Yunusa, Aliyu Umar, Muhammad Lawan. Arxiv 2024.

14. Discrete Diffusion Language Model for Long Text Summarization. Do Huu Dat, Do Duc Anh, Anh Tuan Luu, Wray Buntine. Arxiv 2024.

15. ML-Mamba: Efficient Multi-Modal Large Language Model Utilizing Mamba-2. Wenjun Huang, Jianguo Hu. Arxiv 2024.

16. Jamba-1.5: Hybrid Transformer-Mamba Models at Scale. Jamba Team: Barak Lenz, Alan Arazi, Amir Bergman, Avshalom Manevich, Barak Peleg, Ben Aviram, Chen Almagor, Clara Fridman, Dan Padnos, Daniel Gissin, Daniel Jannai, Dor Muhlgay, Dor Zimberg, Edden M Gerber, Elad Dolev, Eran Krakovsky, Erez Safahi, Erez Schwartz, Gal Cohen, Gal Shachaf, Haim Rozenblum, Hofit Bata, Ido Blass, Inbal Magar, Itay Dalmedigos, Jhonathan Osin, Julie Fadlon, Maria Rozman, Matan Danos, Michael Gokhman, Mor Zusman, Naama Gidron, Nir Ratner, Noam Gat, Noam Rozen, Oded Fried, Ohad Leshno, Omer Antverg, Omri Abend, Opher Lieber, Or Dagan, Orit Cohavi, Raz Alon, Ro'i Belson, Roi Cohen, Rom Gilad, Roman Glozman, Shahar Lev, Shaked Meirom, Tal Delbari, Tal Ness, Tomer Asida, Tom Ben Gal, Tom Braude, Uriya Pumerantz, Yehoshua Cohen, Yonatan Belinkov, Yuval Globerson, Yuval Peleg Levy, Yoav Shoham. Arxiv 2024.

17. Dynamic Chunking for End-to-End Hierarchical Sequence Modeling. Sukjun Hwang, Brandon Wang, Albert Gu. Arxiv 2025.

18. SpikingSSMs: Learning Long Sequences with Sparse and Parallel Spiking State Space Models. Shuaijie Shen, Chao Wang, Renzhuo Huang, Yan Zhong, Qinghai Guo, Zhichao Lu, Jianguo Zhang, Luziwei Leng. Arxiv 2024.

19. ReMamba: Equip Mamba with Effective Long-Sequence Modeling. Danlong Yuan, Jiahao Liu, Bei Li, Huishuai Zhang, Jingang Wang, Xunliang Cai, Dongyan Zhao. Arxiv 2024.

20. Stuffed Mamba: State Collapse and State Capacity of RNN-Based Long-Context Modeling. Yingfa Chen, Xinrong Zhang, Shengding Hu, Xu Han, Zhiyuan Liu, Maosong Sun. Arxiv 2024.

21. Taipan: Efficient and Expressive State Space Language Models with Selective Attention. Chien Van Nguyen, Huy Huu Nguyen, Thang M. Pham, Ruiyi Zhang, Hanieh Deilamsalehy, Puneet Mathur, Ryan A. Rossi, Trung Bui, Viet Dac Lai, Franck Dernoncourt, Thien Huu Nguyen. Arxiv 2024.

22. Rethinking Token Reduction for State Space Models. Zheng Zhan, Yushu Wu, Zhenglun Kong, Changdi Yang, Yifan Gong, Xuan Shen, Xue Lin, Pu Zhao, Yanzhi Wang. EMNLP 2024.

23. Attamba: Attending To Multi-Token States. Yash Akhauri, Safeen Huda, Mohamed S. Abdelfattah. Arxiv 2024.

24. Gated Delta Networks: Improving Mamba2 with Delta Rule. Songlin Yang, Jan Kautz, Ali Hatamizadeh. Arxiv 2024.

25. SSMLoRA: Enhancing Low-Rank Adaptation with State Space Model. Jiayang Yu, Yihang Zhang, Bin Wang, Peiqin Lin, Yongkang Liu, Shi Feng. NAACL 2025.

26. S2TX: Cross-Attention Multi-Scale State-Space Transformer for Time Series Forecasting. Zihao Wu, Juncheng Dong, Haoming Yang, Vahid Tarokh. Arxiv 2025.

27. CacheMamba: Popularity Prediction for Mobile Edge Caching Networks via Selective State Spaces. Ghazaleh Kianfar, Zohreh Hajiakhondi-Meybodi, Arash Mohammadi. Arxiv 2025.

28. M1: Towards Scalable Test-Time Compute with Mamba Reasoning Models. Junxiong Wang, Wen-Ding Li, Daniele Paliotta, Daniel Ritter, Alexander M. Rush, Tri Dao. Arxiv 2025.

29. LongMamba: Enhancing Mamba's Long Context Capabilities via Training-Free Receptive Field Enlargement. Zhifan Ye, Kejing Xia, Yonggan Fu, Xin Dong, Jihoon Hong, Xiangchi Yuan, Shizhe Diao, Jan Kautz, Pavlo Molchanov, Yingyan Celine Lin. Arxiv 2025.

30. RWKV-X: A Linear Complexity Hybrid Language Model. Haowen Hou, Zhiyi Huang, Kaifeng Tan, Rongchang Lu, Fei Richard Yu. Arxiv 2025.

31. Zebra-Llama: Towards Extremely Efficient Hybrid Models. Mingyu Yang, Mehdi Rezagholizadeh, Guihong Li, Vikram Appia, Emad Barsoum. Arxiv 2025.

32. Sparsified State-Space Models are Efficient Highway Networks. Woomin Song, Jihoon Tack, Sangwoo Mo, Seunghyuk Oh, Jinwoo Shin. TMLR 2025.

33. Don't Pay Attention. Mohammad Hammoud, Devang Acharya. Arxiv 2025.

34. A Systematic Analysis of Hybrid Linear Attention. Dustin Wang, Rui-Jie Zhu, Steven Abreu, Yong Shan, Taylor Kergan, Yuqi Pan, Yuhong Chou, Zheng Li, Ge Zhang, Wenhao Huang, Jason Eshraghian. Arxiv 2025.

35. Gated Associative Memory: A Parallel O(N) Architecture for Efficient Sequence Modeling. Rishiraj Acharya. Arxiv 2025.

36. Mamba Modulation: On the Length Generalization of Mamba. Peng Lu, Jerry Huang, Qiuhao Zeng, Xinyu Wang, Boxing Wang, Philippe Langlais, Yufei Cui. NeurIPS 2025.

5. Long-Context LLMs

5.1 Length Extrapolation

1. RoFormer: Enhanced Transformer with Rotary Position Embedding. Jianlin Su, Yu Lu, Shengfeng Pan, Ahmed Murtadha, Bo Wen, Yunfeng Liu. Arxiv 2021.

2. Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation. Ofir Press, Noah A. Smith, Mike Lewis. ICLR 2022.

3. KERPLE: Kernelized Relative Positional Embedding for Length Extrapolation. Ta-Chung Chi, Ting-Han Fan, Peter J. Ramadge, Alexander I. Rudnicky. Arxiv 2022.

4. Dissecting Transformer Length Extrapolation via the Lens of Receptive Field Analysis. Ta-Chung Chi, Ting-Han Fan, Alexander I. Rudnicky, Peter J. Ramadge. ACL 2023.

5. A Length-Extrapolatable Transformer. Yutao Sun, Li Dong, Barun Patra, Shuming Ma, Shaohan Huang, Alon Benhaim, Vishrav Chaudhary, Xia Song, Furu Wei. ACL 2023.

6. Randomized Positional Encodings Boost Length Generalization of Transformers. Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, Joel Veness. ACL 2023.

7. The Impact of Positional Encoding on Length Generalization in Transformers. Amirhossein Kazemnejad, Inkit Padhi, Karthikeyan Natesan Ramamurthy, Payel Das, Siva Reddy. Arxiv 2023.

8. Focused Transformer: Contrastive Training for Context Scaling. Szymon Tworkowski, Konrad Staniszewski, Mikołaj Pacek, Yuhuai Wu, Henryk Michalewski, Piotr Miłoś. Arxiv 2023.

9. Extending Context Window of Large Language Models via Positional Interpolation. Shouyuan Chen, Sherman Wong, Liangjian Chen, Yuandong Tian. Arxiv 2023.

10. Exploring Transformer Extrapolation. Zhen Qin, Yiran Zhong, Hui Deng. Arxiv 2023.

11. LM-Infinite: Simple On-the-Fly Length Generalization for Large Language Models. Chi Han, Qifan Wang, Wenhan Xiong, Yu Chen, Heng Ji, Sinong Wang. Arxiv 2023.

12. YaRN: Efficient Context Window Extension of Large Language Models. Bowen Peng, Jeffrey Quesnelle, Honglu Fan, Enrico Shippole. Arxiv 2023.

13. PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training. Dawei Zhu,Nan Yang,Liang Wang,Yifan Song,Wenhao Wu,Furu Wei,Sujian Li. Arxiv 2023.

14. LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models. Yukang Chen, Shengju Qian, Haotian Tang, Xin Lai, Zhijian Liu, Song Han, Jiaya Jia. ICLR 2024 Oral.

15. Scaling Laws of RoPE-based Extrapolation. Xiaoran Liu, Hang Yan, Shuo Zhang, Chenxin An, Xipeng Qiu, Dahua Lin. Arxiv 2023.

16. Attention Alignment and Flexible Positional Embeddings Improve Transformer Length Extrapolation. Ta-Chung Chi,Ting-Han Fan,Alexander I. Rudnicky. Arxiv 2023.

17. CoCA: Fusing position embedding with Collinear Constrained Attention for fine-tuning free context window extending. Shiyi Zhu, Jing Ye, Wei Jiang, Qi Zhang, Yifan Wu, Jianguo Li. Arxiv 2023.

18. Structured Packing in LLM Training Improves Long Context Utilization. Konrad Staniszewski, Szymon Tworkowski, Sebastian Jaszczur, Henryk Michalewski, Łukasz Kuciński, Piotr Miłoś. Arxiv 2024.

19. LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning. Hongye Jin, Xiaotian Han, Jingfeng Yang, Zhimeng Jiang, Zirui Liu, Chia-Yuan Chang, Huiyuan Chen, Xia Hu. Arxiv 2024.

20. Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache. Bin Lin, Tao Peng, Chen Zhang, Minmin Sun, Lanbo Li, Hanyu Zhao, Wencong Xiao, Qi Xu, Xiafei Qiu, Shen Li, Zhigang Ji, Yong Li, Wei Lin. Arxiv 2024.

21. Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models. Zhen Qin, Weigao Sun, Dong Li, Xuyang Shen, Weixuan Sun, Yiran Zhong. Arxiv 2024.

22. Extending LLMs' Context Window with 100 Samples. Yikai Zhang, Junlong Li, Pengfei Liu. Arxiv 2024.

23. E^2-LLM: Efficient and Extreme Length Extension of Large Language Models. Jiaheng Liu, Zhiqi Bai, Yuanxing Zhang, Chenchen Zhang, Yu Zhang, Ge Zhang, Jiakai Wang, Haoran Que, Yukang Chen, Wenbo Su, Tiezheng Ge, Jie Fu, Wenhu Chen, Bo Zheng. Arxiv 2024.

24. With Greater Text Comes Greater Necessity: Inference-Time Training Helps Long Text Generation. Y. Wang, D. Ma, D. Cai. Arxiv 2024.

25. Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation. Zhenyu He, Guhao Feng, Shengjie Luo, Kai Yang, Di He, Jingjing Xu, Zhi Zhang, Hongxia Yang, Liwei Wang. ICML 2024.

26. Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens. Jiacheng Liu, Sewon Min, Luke Zettlemoyer, Yejin Choi, Hannaneh Hajishirzi. Arxiv 2024.

27. LongRoPE: Extending LLM ContextWindow Beyond 2 Million Tokens. Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, Yuanyuan Xu, Ning Shang, Jiahang Xu, Fan Yang, Mao Yang. Arxiv 2024.

28. Data Engineering for Scaling Language Models to 128K Context. Yao Fu, Rameswar Panda, Xinyao Niu, Xiang Yue, Hannaneh Hajishirzi, Yoon Kim, Hao Peng. Arxiv 2024.

29. Transformers Can Achieve Length Generalization But Not Robustly. Yongchao Zhou, Uri Alon, Xinyun Chen, Xuezhi Wang, Rishabh Agarwal, Denny Zhou. Arxiv 2024.

30. Long-Context Language Modeling with Parallel Context Encoding. Howard Yen, Tianyu Gao, Danqi Chen. ACL 2024.

31. CLEX: Continuous Length Extrapolation for Large Language Models. Guanzheng Chen, Xin Li, Zaiqiao Meng, Shangsong Liang, Lidong Bing. Arxiv 2023.

32. Resonance RoPE: Improving Context Length Generalization of Large Language Models. Suyuchen Wang, Ivan Kobyzev, Peng Lu, Mehdi Rezagholizadeh, Bang Liu. Arxiv 2024.

33. Can't Remember Details in Long Documents? You Need Some R&R. Devanshu Agrawal, Shang Gao, Martin Gajek. Arxiv 2024.

34. Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding. Zhenyu Zhang, Runjin Chen, Shiwei Liu, Zhewei Yao, Olatunji Ruwase, Beidi Chen, Xiaoxia Wu, Zhangyang Wang. Arxiv 2024.

35. InfLLM: Unveiling the Intrinsic Capacity of LLMs for Understanding Extremely Long Sequences with Training-Free Memory. Chaojun Xiao, Pengle Zhang, Xu Han, Guangxuan Xiao, Yankai Lin, Zhengyan Zhang, Zhiyuan Liu, Song Han, Maosong Sun. Arxiv 2024.

36. Naive Bayes-based Context Extension for Large Language Models. Jianlin Su, Murtadha Ahmed, Wenbo, Luo Ao, Mingren Zhu, Yunfeng Liu. Arxiv 2024.

37. Keyformer: KV Cache Reduction through Key Tokens Selection for Efficient Generative Inference. Muhammad Adnan, Akhil Arunkumar, Gaurav Jain, Prashant J. Nair, Ilya Soloveychik, Purushotham Kamath. Arxiv 2024.

38. In-Context Pretraining: Language Modeling Beyond Document Boundaries. Weijia Shi, Sewon Min, Maria Lomeli, Chunting Zhou, Margaret Li, Xi Victoria Lin, Noah A. Smith, Luke Zettlemoyer, Wen-tau Yih, Mike Lewis. ICLR 2024 Spotlight.

39. Effective Long-Context Scaling of Foundation Models. Wenhan Xiong, Jingyu Liu, Igor Molybog, Hejia Zhang, Prajjwal Bhargava, Rui Hou, Louis Martin, Rashi Rungta, Karthik Abinav Sankararaman, Barlas Oguz, Madian Khabsa, Han Fang, Yashar Mehdad, Sharan Narang, Kshitiz Malik, Angela Fan, Shruti Bhosale, Sergey Edunov, Mike Lewis, Sinong Wang, Hao Ma. Arxiv 2023.

40. Fewer Truncations Improve Language Modeling. Hantian Ding, Zijian Wang, Giovanni Paolini, Varun Kumar, Anoop Deoras, Dan Roth, Stefano Soatto. Arxiv 2024.

41. Length Generalization of Causal Transformers without Position Encoding. Jie Wang, Tao Ji, Yuanbin Wu, Hang Yan, Tao Gui, Qi Zhang, Xuanjing Huang, Xiaoling Wang. Arxiv 2024.

42. Extending Llama-3's Context Ten-Fold Overnight. Peitian Zhang, Ninglu Shao, Zheng Liu, Shitao Xiao, Hongjin Qian, Qiwei Ye, Zhicheng Dou. Arxiv 2024.

43. Long Context Alignment with Short Instructions and Synthesized Positions. Wenhao Wu, Yizhong Wang, Yao Fu, Xiang Yue, Dawei Zhu, Sujian Li. Arxiv 2024.

44. xLSTM: Extended Long Short-Term Memory. Maximilian Beck, Korbinian Pöppel, Markus Spanring, Andreas Auer, Oleksandra Prudnikova, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter. Arxiv 2024.

45. DAPE: Data-Adaptive Positional Encoding for Length Extrapolation. Chuanyang Zheng, Yihang Gao, Han Shi, Minbin Huang, Jingyao Li, Jing Xiong, Xiaozhe Ren, Michael Ng, Xin Jiang, Zhenguo Li, Yu Li. NeurIPS 2024.

46. Contextual Position Encoding: Learning to Count What's Important. Olga Golovneva, Tianlu Wang, Jason Weston, Sainbayar Sukhbaatar. Arxiv 2024.

47. Quest: Query-centric Data Synthesis Approach for Long-context Scaling of Large Language Model. Chaochen Gao, Xing Wu, Qi Fu, Songlin Hu. Arxiv 2024.

48. Position Coupling: Improving Length Generalization of Arithmetic Transformers Using Task Structure. Hanseul Cho, Jaeyoung Cha, Pranjal Awasthi, Srinadh Bhojanapalli, Anupam Gupta, Chulhee Yun. NeurIPS 2024.

49. LongSkywork: A Training Recipe for Efficiently Extending Context Length in Large Language Models. Liang Zhao, Tianwen Wei, Liang Zeng, Cheng Cheng, Liu Yang, Peng Cheng, Lijie Wang, Chenxia Li, Xuejie Wu, Bo Zhu, Yimeng Gan, Rui Hu, Shuicheng Yan, Han Fang, Yahui Zhou. Arxiv 2024.

50. Explicitly Encoding Structural Symmetry is Key to Length Generalization in Arithmetic Tasks. Mahdi Sabbaghi, George Pappas, Hamed Hassani, Surbhi Goel. Arxiv 2024.

51. An Efficient Recipe for Long Context Extension via Middle-Focused Positional Encoding. Tong Wu, Yanpeng Zhao, Zilong Zheng. NeurIPS 2024.

52. 3D-RPE: Enhancing Long-Context Modeling Through 3D Rotary Position Encoding. Xindian Ma, Wenyuan Liu, Peng Zhang, Nan Xu. Arxiv 2024.

53. Mixture of In-Context Experts Enhance LLMs' Long Context Awareness. Hongzhan Lin, Ang Lv, Yuhan Chen, Chen Zhu, Yang Song, Hengshu Zhu, Rui Yan. Arxiv 2024.

54. Human-like Episodic Memory for Infinite Context LLMs. Zafeirios Fountas, Martin A Benfeghoul, Adnan Oomerjee, Fenia Christopoulou, Gerasimos Lampouras, Haitham Bou-Ammar, Jun Wang. Arxiv 2024.

55. Scaling Granite Code Models to 128K Context. Matt Stallone, Vaibhav Saxena, Leonid Karlinsky, Bridget McGinn, Tim Bula, Mayank Mishra, Adriana Meza Soria, Gaoyuan Zhang, Aditya Prasad, Yikang Shen, Saptha Surendran, Shanmukha Guttula, Hima Patel, Parameswaran Selvam, Xuan-Hong Dang, Yan Koyfman, Atin Sood, Rogerio Feris, Nirmit Desai, David D. Cox, Ruchir Puri, Rameswar Panda. Arxiv 2024.

56. ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities. Peng Xu, Wei Ping, Xianchao Wu, Zihan Liu, Mohammad Shoeybi, Bryan Catanzaro. Arxiv 2024.

57. Efficient Solutions For An Intriguing Failure of LLMs: Long Context Window Does Not Mean LLMs Can Analyze Long Sequences Flawlessly. Peyman Hosseini, Ignacio Castro, Iacopo Ghinassi, Matthew Purver. Arxiv 2024.

58. FocusLLM: Scaling LLM's Context by Parallel Decoding. Zhenyu Li, Yike Zhang, Tengyu Pan, Yutao Sun, Zhichao Duan, Junjie Fang, Rong Han, Zixuan Wang, Jianyong Wang. Arxiv 2024.

59. LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models. Zhiyuan Hu, Yuliang Liu, Jinman Zhao, Suyuchen Wang, Yan Wang, Wei Shen, Qing Gu, Anh Tuan Luu, See-Kiong Ng, Zhiwei Jiang, Bryan Hooi. Arxiv 2024.

60. E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning. Zihan Liao, Jun Wang, Hang Yu, Lingxiao Wei, Jianguo Li, Jun Wang, Wei Zhang. Arxiv 2024.

61. Untie the Knots: An Efficient Data Augmentation Strategy for Long-Context Pre-Training in Language Models. Junfeng Tian, Da Zheng, Yang Cheng, Rui Wang, Colin Zhang, Debing Zhang. Arxiv 2024.

62. PEAR: Position-Embedding-Agnostic Attention Re-weighting Enhances Retrieval-Augmented Generation with Zero Inference Overhead. Tao Tan, Yining Qian, Ang Lv, Hongzhan Lin, Songhao Wu, Yongbo Wang, Feng Wang, Jingtong Wu, Xin Lu, Rui Yan. Arxiv 2024.

63. Efficient Long-range Language Modeling with Self-supervised Causal Retrieval. Xiang Hu, Zhihao Teng, Wei Wu, Kewei Tu. Arxiv 2024.

64. A Little Goes a Long Way: Efficient Long Context Training and Inference with Partial Contexts. Suyu Ge, Xihui Lin, Yunan Zhang, Jiawei Han, Hao Peng. Arxiv 2024.

65. Extending Context Window of Large Language Models from a Distributional Perspective. Yingsheng Wu, Yuxuan Gu, Xiaocheng Feng, Weihong Zhong, Dongliang Xu, Qing Yang, Hongtao Liu, Bing Qin. Arxiv 2024.

66. How to Train Long-Context Language Models (Effectively). Tianyu Gao, Alexander Wettig, Howard Yen, Danqi Chen. Arxiv 2024.

67. Differential Transformer. Tianzhu Ye, Li Dong, Yuqing Xia, Yutao Sun, Yi Zhu, Gao Huang, Furu Wei. Arxiv 2024.

68. DAPE V2: Process Attention Score as Feature Map for Length Extrapolation. Chuanyang Zheng, Yihang Gao, Han Shi, Jing Xiong, Jiankai Sun, Jingyao Li, Minbin Huang, Xiaozhe Ren, Michael Ng, Xin Jiang, Zhenguo Li, Yu Li. Arxiv 2024.

69. Why Does the Effective Context Length of LLMs Fall Short?. Chenxin An, Jun Zhang, Ming Zhong, Lei Li, Shansan Gong, Yao Luo, Jingjing Xu, Lingpeng Kong. Arxiv 2024.

70. LOGO -- Long cOntext aliGnment via efficient preference Optimization. Zecheng Tang, Zechen Sun, Juntao Li, Qiaoming Zhu, Min Zhang. [ICML 2025].

71. Selecting Influential Samples for Long Context Alignment via Homologous Models' Guidance and Contextual Awareness Measurement. Shuzheng Si, Haozhe Zhao, Gang Chen, Yunshui Li, Kangyang Luo, Chuancheng Lv, Kaikai An, Fanchao Qi, Baobao Chang, Maosong Sun. Arxiv 2024.

72. Two are better than one: Context window extension with multi-grained self-injection. Wei Han, Pan Zhou, Soujanya Poria, Shuicheng Yan. Arxiv 2024.

73. LongReward: Improving Long-context Large Language Models with AI Feedback. Jiajie Zhang, Zhongni Hou, Xin Lv, Shulin Cao, Zhenyu Hou, Yilin Niu, Lei Hou, Yuxiao Dong, Ling Feng, Juanzi Li. Arxiv 2024.

74. HoPE: A Novel Positional Encoding Without Long-Term Decay for Enhanced Context Awareness and Extrapolation. Yuhan Chen, Ang Lv, Jian Luan, Bin Wang, Wei Liu. Arxiv 2024.

75. What is Wrong with Perplexity for Long-context Language Modeling?. Lizhe Fang, Yifei Wang, Zhaoyang Liu, Chenheng Zhang, Stefanie Jegelka, Jinyang Gao, Bolin Ding, Yisen Wang. Arxiv 2024.

76. Circuit Complexity Bounds for RoPE-based Transformer Architecture. Bo Chen, Xiaoyu Li, Yingyu Liang, Jiangxuan Long, Zhenmei Shi, Zhao Song. Arxiv 2024.

77. Large Language Models Can Self-Improve in Long-context Reasoning. Siheng Li, Cheng Yang, Zesen Cheng, Lemao Liu, Mo Yu, Yujiu Yang, Wai Lam. Arxiv 2024.

78. Transformers Can Do Arithmetic with the Right Embeddings. Sean Michael McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein. NeurIPS 2024.

79. Arithmetic Transformers Can Length-Generalize in Both Operand Length and Count. Hanseul Cho, Jaeyoung Cha, Srinadh Bhojanapalli, Chulhee Yun. Arxiv 2024.

80. Breaking the Stage Barrier: A Novel Single-Stage Approach to Long Context Extension for Large Language Models. Haoran Lian, Junmin Chen, Wei Huang, Yizhe Xiong, Wenping Hu, Guiguang Ding, Hui Chen, Jianwei Niu, Zijia Lin, Fuzheng Zhang, Di Zhang. Arxiv 2024.

81. Attention Entropy is a Key Factor: An Analysis of Parallel Context Encoding with Full-attention-based Pre-trained Language Models. Zhisong Zhang, Yan Wang, Xinting Huang, Tianqing Fang, Hongming Zhang, Chenlong Deng, Shuaiyi Li, Dong Yu. Arxiv 2024.

82. DCIS: Efficient Length Extrapolation of LLMs via Divide-and-Conquer Scaling Factor Search. Lei Yang, Shaoyang Xu, Deyi Xiong. Arxiv 2024.

83. Adjoint sharding for very long context training of state space models. Xingzi Xu, Amir Tavanaei, Kavosh Asadi, Karim Bouyarmane. Arxiv 2025.

84. Information Entropy Invariance: Enhancing Length Extrapolation in Attention Mechanisms. Kewei Li, Yanwen Kong, Yiping Xu, Lan Huang, Ruochi Zhang, Fengfeng Zhou. Arxiv 2025.

85. LeMo: Enabling LEss Token Involvement for MOre Context Fine-tuning. Tuowei Wang, Xingyu Chen, Kun Li, Ting Cao, Ju Ren, Yaoxue Zhang. Arxiv 2025.

86. NExtLong: Toward Effective Long-Context Training without Long Documents. Chaochen Gao, Xing Wu, Zijia Lin, Debing Zhang, Songlin Hu. Arxiv 2025.

87. SEAL: Scaling to Emphasize Attention for Long-Context Retrieval. Changhun Lee, Jun-gyu Jin, Younghyun Cho, Eunhyeok Park. Arxiv 2025.

88. DINT Transformer. Yueyang Cang, Yuhang Liu, Xiaoteng Zhang, Erlu Zhao, Li Shi. Arxiv 2025.

89. Scalable-Softmax Is Superior for Attention. Ken M. Nakanishi. Arxiv 2025.

90. Rope to Nope and Back Again: A New Hybrid Attention Strategy. Bowen Yang, Bharat Venkitesh, Dwarak Talupuru, Hangyu Lin, David Cairuz, Phil Blunsom, Acyr Locatelli. Arxiv 2025.

91. A Training-Free Length Extrapolation Approach for LLMs: Greedy Attention Logit Interpolation (GALI). Yan Li, Tianyi Zhang, Zechuan Li, Soyeon Caren Han. Arxiv 2025.

92. LongReD: Mitigating Short-Text Degradation of Long-Context Large Language Models via Restoration Distillation. Zican Dong, Junyi Li, Jinhao Jiang, Mingyu Xu, Wayne Xin Zhao, Bingning Wang, Weipeng Chen. Arxiv 2025.

93. Unveiling Simplicities of Attention: Adaptive Long-Context Head Identification. Konstantin Donhauser, Charles Arnal, Mohammad Pezeshki, Vivien Cabannes, David Lopez-Paz, Kartik Ahuja. Arxiv 2025.

94. The Rotary Position Embedding May Cause Dimension Inefficiency in Attention Heads for Long-Distance Retrieval. Ting-Rui Chiang, Dani Yogatama. Arxiv 2025.

95. LongFaith: Enhancing Long-Context Reasoning in LLMs with Faithful Synthetic Data. Cehao Yang, Xueyuan Lin, Chengjin Xu, Xuhui Jiang, Shengjie Ma, Aofan Liu, Hui Xiong, Jian Guo. Arxiv 2025.

96. LongPO: Long Context Self-Evolution of Large Language Models through Short-to-Long Preference Optimization. Guanzheng Chen, Xin Li, Michael Qizhe Shieh, Lidong Bing. Arxiv 2025.

97. ParallelComp: Parallel Long-Context Compressor for Length Extrapolation. Jing Xiong, Jianghan Shen, Chuanyang Zheng, Zhongwei Wan, Chenyang Zhao, Chiwun Yang, Fanghua Ye, Hongxia Yang, Lingpeng Kong, Ngai Wong. ICML 2025.

98. Generalizing From Short to Long: Effective Data Synthesis for Long-Context Instruction Tuning. Wenhao Zhu, Pinzhen Chen, Hanxu Hu, Shujian Huang, Fei Yuan, Jiajun Chen, Alexandra Birch. Arxiv 2025.

99. LongAttn: Selecting Long-context Training Data via Token-level Attention. Longyun Wu, Dawei Zhu, Guangxiang Zhao, Zhuocheng Yu, Junfeng Ran, Xiangyu Wong, Lin Sun, Sujian Li. Arxiv 2025.

100. WildLong: Synthesizing Realistic Long-Context Instruction Data at Scale. Jiaxi Li, Xingxing Zhang, Xun Wang, Xiaolong Huang, Li Dong, Liang Wang, Si-Qing Chen, Wei Lu, Furu Wei. Arxiv 2025.

101. Sliding Window Attention Training for Efficient Large Language Models. Zichuan Fu, Wentao Song, Yejing Wang, Xian Wu, Yefeng Zheng, Yingying Zhang, Derong Xu, Xuetao Wei, Tong Xu, Xiangyu Zhao. Arxiv 2025.

102. LongRoPE2: Near-Lossless LLM Context Window Scaling. Ning Shang, Li Lyna Zhang, Siyuan Wang, Gaokai Zhang, Gilsinia Lopez, Fan Yang, Weizhu Chen, Mao Yang. Arxiv 2025.

103. ByteScale: Efficient Scaling of LLM Training with a 2048K Context Length on More Than 12,000 GPUs. Hao Ge, Junda Feng, Qi Huang, Fangcheng Fu, Xiaonan Nie, Lei Zuo, Haibin Lin, Bin Cui, Xin Liu. Arxiv 2025.

104. Pause-Tuning for Long-Context Comprehension: A Lightweight Approach to LLM Attention Recalibration. James Begin, Namit Agrawal, Eshan Singh, Yicheng Fu, Sean O'Brien, Vasu Sharma, Kevin Zhu. Arxiv 2025.

105. LADM: Long-context Training Data Selection with Attention-based Dependency Measurement for LLMs. Jianghao Chen, Junhong Wu, Yangyifan Xu, Jiajun Zhang. Arxiv 2025.

106. Forgetting Transformer: Softmax Attention with a Forget Gate. Zhixuan Lin, Evgenii Nikishin, Xu Owen He, Aaron Courville. ICLR 2025.

107. Layer-Specific Scaling of Positional Encodings for Superior Long-Context Modeling. Zhenghua Wang, Yiran Ding, Changze Lv, Zhibo Xu, Tianlong Li, Tianyuan Shi, Xiaoqing Zheng, Xuanjing Huang. Arxiv 2025.

108. Token Weighting for Long-Range Language Modeling. Falko Helm, Nico Daheim, Iryna Gurevych. NAACL 2025.

109. From 128K to 4M: Efficient Training of Ultra-Long Context Large Language Models. Chejian Xu, Wei Ping, Peng Xu, Zihan Liu, Boxin Wang, Mohammad Shoeybi, Bo Li, Bryan Catanzaro. Arxiv 2025.

110. SWAN-GPT: An Efficient and Scalable Approach for Long-Context Language Modeling. Krishna C. Puvvada, Faisal Ladhak, Santiago Akle Serrano, Cheng-Ping Hsieh, Shantanu Acharya, Somshubra Majumdar, Fei Jia, Samuel Kriman, Simeng Sun, Dima Rekesh, Boris Ginsburg. Arxiv 2025.

111. Scaling Instruction-Tuned LLMs to Million-Token Contexts via Hierarchical Synthetic Data Generation. Linda He, Jue Wang, Maurice Weber, Shang Zhu, Ben Athiwaratkun, Ce Zhang. Arxiv 2025.

112. Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation. Yi Lu, Wanxu Zhao, Xin Zhou, Chenxin An, Chenglong Wang, Shuo Li, Yuming Yang, Jun Zhao, Tao Ji, Tao Gui, Qi Zhang, Xuanjing Huang. Arxiv 2025.

113. SELF: Self-Extend the Context Length With Logistic Growth Function. Phat Thanh Dang, Saahil Thoppay, Wang Yang, Qifan Wang, Vipin Chaudhary, Xiaotian Han. Arxiv 2025.

114. Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs. Woomin Song, Seunghyuk Oh, Sangwoo Mo, Jaehyung Kim, Sukmin Yun, Jung-Woo Ha, Jinwoo Shin. ICLR 2024.

115. Compress, Gather, and Recompute: REFORMing Long-Context Processing in Transformers. Woomin Song, Sai Muralidhar Jayanthi, Srikanth Ronanki, Kanthashree Mysore Sathyendra, Jinwoo Shin, Aram Galstyan, Shubham Katiyar, Sravan Babu Bodapati. Arxiv 2025.

116. Mitigating Posterior Salience Attenuation in Long-Context LLMs with Positional Contrastive Decoding. Zikai Xiao, Ziyang Wang, Wen Ma, Yan Zhang, Wei Shen, Yan Wang, Luqi Gong, Zuozhu Liu. Arxiv 2025.

117. Long-Short Alignment for Effective Long-Context Modeling in LLMs. Tianqi Du, Haotian Huang, Yifei Wang, Yisen Wang. Arxiv 2025.

118. Arctic Long Sequence Training: Scalable And Efficient Training For Multi-Million Token Sequences. Stas Bekman, Samyam Rajbhandari, Michael Wyatt, Jeff Rasley, Tunji Ruwase, Zhewei Yao, Aurick Qiao, Yuxiong He. Arxiv 2025.

119. Long-Context Generalization with Sparse Attention. Pavlo Vasylenko, Marcos Treviso, André F. T. Martins. Arxiv 2025.

120. Bayesian Attention Mechanism: A Probabilistic Framework for Positional Encoding and Context Length Extrapolation. Arthur S. Bianchessi, Rodrigo C. Barros, Lucas S. Kupssinskü Arxiv 2025.

121. HoPE: Hyperbolic Rotary Positional Encoding for Stable Long-Range Dependency Modeling in Large Language Models. Chang Dai, Hongyu Shan, Mingyang Song, Di Liang. Arxiv 2025.

122. Causal Attention with Lookahead Keys. Zhuoqing Song, Peng Sun, Huizhuo Yuan, Quanquan Gu. Arxiv 2025.

123. Positional Encoding via Token-Aware Phase Attention. Yu, Wang, Sheng Shen, Rémi Munos, Hongyuan Zhan, Yuandong Tian. Arxiv 2025.

124. Extending the Context of Pretrained LLMs by Dropping Their Positional Embeddings (DroPE). Yoav Gelberg, Koshi Eguchi, Takuya Akiba, Edoardo Cetin. Arxiv 2025.

125. RePo: Language Models with Context Re-Positioning. Huayang Li, Tianyu Zhao, Richard Sproat. Arxiv 2025.

5.2 Test-Time Training

1. Let's (not) just put things in Context: Test-Time Training for Long-Context LLMs. Rachit Bansal, Aston Zhang, Rishabh Tiwari, Lovish Madaan, Sai Surya Duvvuri, Devvrit Khatri, David Brandfonbrener, David Alvarez-Melis, Prajjwal Bhargava, Mihir Sanjay Kale, Samy Jelassi. Arxiv 2025.

6. Long Term Memory

1. Unleashing Infinite-Length Input Capacity for Large-scale Language Models with Self-Controlled Memory System. Xinnian Liang, Bing Wang, Hui Huang, Shuangzhi Wu, Peihao Wu, Lu Lu, Zejun Ma, Zhoujun Li. Arxiv 2023.

2. MemoryBank: Enhancing Large Language Models with Long-Term Memory. Wanjun Zhong, Lianghong Guo, Qiqi Gao, He Ye, Yanlin Wang. Arxiv 2023.

3. Improve Long-term Memory Learning Through Rescaling the Error Temporally. Shida Wang, Zhanglu Yan. Arxiv 2023.

4. Recursively Summarizing Enables Long-Term Dialogue Memory in Large Language Models. Qingyue Wang, Liang Ding, Yanan Cao, Zhiliang Tian, Shi Wang, Dacheng Tao, Li Guo. Arxiv 2023.

5. Empowering Working Memory for Large Language Model Agents. Jing Guo, Nan Li, Jianchuan Qi, Hang Yang, Ruiqiao Li, Yuzhen Feng, Si Zhang, Ming Xu. Arxiv 2024.

6. Evolving Large Language Model Assistant with Long-Term Conditional Memory. Ruifeng Yuan, Shichao Sun, Zili Wang, Ziqiang Cao, Wenjie Li. Arxiv 2024.

7. Commonsense-augmented Memory Construction and Management in Long-term Conversations via Context-aware Persona Refinement. Hana Kim, Kai Tzu-iunn Ong, Seoyeon Kim, Dongha Lee, Jinyoung Yeo. Arxiv 2024.

8. A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts. Kuang-Huei Lee, Xinyun Chen, Hiroki Furuta, John Canny, Ian Fischer. Arxiv 2024.

9. Steering Conversational Large Language Models for Long Emotional Support Conversations. Navid Madani, Sougata Saha, Rohini Srihari. Arxiv 2024.

10. SPAR: Personalized Content-Based Recommendation via Long Engagement Attention. Chiyu Zhang, Yifei Sun, Jun Chen, Jie Lei, Muhammad Abdul-Mageed, Sinong Wang, Rong Jin, Sem Park, Ning Yao, Bo Long. Arxiv 2024.

11. Compress to Impress: Unleashing the Potential of Compressive Memory in Real-World Long-Term Conversations. Nuo Chen, Hongguang Li, Juhua Huang, Baoyuan Wang, Jia Li. Arxiv 2024.

12. StreamingDialogue: Prolonged Dialogue Learning via Long Context Compression with Minimal Losses. Jia-Nan Li, Quan Tu, Cunli Mao, Zhengtao Yu, Ji-Rong Wen, Rui Yan. Arxiv 2024.

13. Prompts As Programs: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization. Tobias Schnabel, Jennifer Neville. Arxiv 2024.

14. HMT: Hierarchical Memory Transformer for Long Context Language Processing. Tobias Schnabel, Jennifer Neville. Arxiv 2024.

15. SirLLM: Streaming Infinite Retentive LLM. Yao Yao, Zuchao Li, Hai Zhao. Arxiv 2024.

16. Toward Conversational Agents with Context and Time Sensitive Long-term Memory. Nick Alonso, Tomás Figliolia, Anthony Ndirango, Beren Millidge. Arxiv 2024.

17. Position Debiasing Fine-Tuning for Causal Perception in Long-Term Dialogue. Shixuan Fan, Wei Wei, Wendi Li, Xian-Ling Mao, Wenfeng Xie, Dangyang Chen. Arxiv 2024.

18. Enhancing Long-Term Memory using Hierarchical Aggregate Tree for Retrieval Augmented Generation. Aadharsh Aadhithya A, Sachin Kumar S, Soman K.P. Arxiv 2024.

19. Suri: Multi-constraint Instruction Following for Long-form Text Generation. Chau Minh Pham, Simeng Sun, Mohit Iyyer. Arxiv 2024.

20. HiAgent: Hierarchical Working Memory Management for Solving Long-Horizon Agent Tasks with Large Language Model. Mengkang Hu, Tianxing Chen, Qiguang Chen, Yao Mu, Wenqi Shao, Ping Luo. Arxiv 2024.

21. CreDes: Causal Reasoning Enhancement and Dual-End Searching for Solving Long-Range Reasoning Problems using LLMs. Kangsheng Wang, Xiao Zhang, Hao Liu, Songde Han, Huimin Ma, Tianyu Hu. Arxiv 2024.

22. CarMem: Enhancing Long-Term Memory in LLM Voice Assistants through Category-Bounding. Johannes Kirmayr, Lukas Stappen, Phillip Schneider, Florian Matthes, Elisabeth André. COLING 2025.

23. M+: Extending MemoryLLM with Scalable Long-Term Memory. Yu Wang, Dmitry Krotov, Yuanzhe Hu, Yifan Gao, Wangchunshu Zhou, Julian McAuley, Dan Gutfreund, Rogerio Feris, Zexue He. Arxiv 2025.

24. LM2: Large Memory Models. Jikun Kang, Wenqi Wu, Filippos Christianos, Alex J. Chan, Fraser Greenlee, George Thomas, Marvin Purtorab, Andy Toulis. Arxiv 2025.        

25. Position: Episodic Memory is the Missing Piece for Long-Term LLM Agents. Mathis Pink, Qinyuan Wu, Vy Ai Vo, Javier Turek, Jianing Mu, Alexander Huth, Mariya Toneva. Arxiv 2025.

26. MEMORYLLM: Towards Self-Updatable Large Language Models. Yu Wang, Yifan Gao, Xiusi Chen, Haoming Jiang, Shiyang Li, Jingfeng Yang, Qingyu Yin, Zheng Li, Xian Li, Bing Yin, Jingbo Shang, Julian McAuley. ICML 2024.

27. Towards LifeSpan Cognitive Systems. Yu Wang, Chi Han, Tongtong Wu, Xiaoxin He, Wangchunshu Zhou, Nafis Sadeq, Xiusi Chen, Zexue He, Wei Wang, Gholamreza Haffari, Heng Ji, Julian McAuley. TMLR 2024.

28. EpMAN: Episodic Memory AttentioN for Generalizing to Longer Contexts. Subhajit Chaudhury, Payel Das, Sarathkrishna Swaminathan, Georgios Kollias, Elliot Nelson, Khushbu Pahwa, Tejaswini Pedapati, Igor Melnyk, Matthew Riemer. Arxiv 2025.

29. Can Memory-Augmented Language Models Generalize on Reasoning-in-a-Haystack Tasks?. Payel Das, Ching-Yun Ko, Sihui Dai, Georgios Kollias, Subhajit Chaudhury, Aurelie Lozano. Arxiv 2025.

30. InfiniteICL: Breaking the Limit of Context Window Size via Long Short-term Memory Transformation. Bowen Cao, Deng Cai, Wai Lam. Arxiv 2025.

31. Cognitive Memory in Large Language Models. Lianlei Shan, Shixian Luo, Zezhou Zhu, Yu Yuan, Yong Wu. Arxiv 2025.

32. MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent. Hongli Yu, Tinghong Chen, Jiangtao Feng, Jiangjie Chen, Weinan Dai, Qiying Yu, Ya-Qin Zhang, Wei-Ying Ma, Jingjing Liu, Mingxuan Wang, Hao Zhou. Arxiv 2025.

33. Explore with Long-term Memory: A Benchmark and Multimodal LLM-based Reinforcement Learning Framework for Embodied Exploration. Sen Wang, Bangwei Liu, Zhenkun Gao, Lizhuang Ma, Xuhong Wang, Yuan Xie, Xin Tan. Arxiv 2026.

34. Fast-weight Product Key Memory. Tianyu Zhao, Llion Jones. Arxiv 2026.

7. RAG and ICL

1. Walking Down the Memory Maze: Beyond Context Limit through Interactive Reading. Howard Chen, Ramakanth Pasunuru, Jason Weston, Asli Celikyilmaz. Arxiv 2023.

2. Attendre: Wait To Attend By Retrieval With Evicted Queries in Memory-Based Transformers for Long Context Processing. Zi Yang, Nan Hua. Arxiv 2024.

3. BGE Landmark Embedding: A Chunking-Free Embedding Method For Retrieval Augmented Long-Context Large Language Models. Kun Luo, Zheng Liu, Shitao Xiao, Kang Liu. Arxiv 2024.

4. Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity. Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang, Jong C. Park. Arxiv 2024.

5. RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation. Chi-Min Chan, Chunpu Xu, Ruibin Yuan, Hongyin Luo, Wei Xue, Yike Guo, Jie Fu. Arxiv 2024.

6. Improving Retrieval Augmented Open-Domain Question-Answering with Vectorized Contexts. Zhuo Chen, Xinyu Wang, Yong Jiang, Pengjun Xie, Fei Huang, Kewei Tu. Arxiv 2024.

7. Superposition Prompting: Improving and Accelerating Retrieval-Augmented Generation. Thomas Merth, Qichen Fu, Mohammad Rastegari, Mahyar Najibi. Arxiv 2024.

8. Multi-view Content-aware Indexing for Long Document Retrieval. Kuicai Dong, Derrick Goh Xin Deik, Yi Quan Lee, Hao Zhang, Xiangyang Li, Cong Zhang, Yong Liu. Arxiv 2024.

9. Retrieval Head Mechanistically Explains Long-Context Factuality. Wenhao Wu, Yizhong Wang, Guangxuan Xiao, Hao Peng, Yao Fu. Arxiv 2024.

10. FlashBack:Efficient Retrieval-Augmented Language Modeling for Long Context Inference. Runheng Liu, Xingchen Xiao, Heyan Huang, Zewen Chi, Zhijing Wu. Arxiv 2024.

11. Feature-Adaptive and Data-Scalable In-Context Learning. Jiahao Li, Quan Wang, Licheng Zhang, Guoqing Jin, Zhendong Mao. Arxiv 2024.

12. KG-RAG: Bridging the Gap Between Knowledge and Creativity. Diego Sanmartin. Arxiv 2024.

13. HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models. Bernal Jiménez Gutiérrez, Yiheng Shu, Yu Gu, Michihiro Yasunaga, Yu Su. Arxiv 2024.

14. Implicit In-context Learning. Zhuowei Li, Zihao Xu, Ligong Han, Yunhe Gao, Song Wen, Di Liu, Hao Wang, Dimitris N. Metaxas. Arxiv 2024.

15. Are Long-LLMs A Necessity For Long-Context Tasks?. Hongjin Qian, Zheng Liu, Peitian Zhang, Kelong Mao, Yujia Zhou, Xu Chen, Zhicheng Dou. Arxiv 2024.

16. Accelerating Inference of Retrieval-Augmented Generation via Sparse Context Selection. Yun Zhu, Jia-Chen Gu, Caitlin Sikora, Ho Ko, Yinxiao Liu, Chu-Cheng Lin, Lei Shu, Liangchen Luo, Lei Meng, Bang Liu, Jindong Chen. Arxiv 2024.

17. Is In-Context Learning Sufficient for Instruction Following in LLMs?. Hao Zhao, Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion. Arxiv 2024.

18. FragRel: Exploiting Fragment-level Relations in the External Memory of Large Language Models. Xihang Yue, Linchao Zhu, Yi Yang. Arxiv 2024.

19. Multi-Head RAG: Solving Multi-Aspect Problems with LLMs. Maciej Besta, Ales Kubicek, Roman Niggli, Robert Gerstenberger, Lucas Weitzendorf, Mingyuan Chi, Patrick Iff, Joanna Gajda, Piotr Nyczyk, Jürgen Müller, Hubert Niewiadomski, Marcin Chrapek, Michał Podstawski, Torsten Hoefler. Arxiv 2024.

20. Demonstration Notebook: Finding the Most Suited In-Context Learning Example from Interactions. Yiming Tang, Bin Dong. Arxiv 2024.

21. Retrieval Meets Reasoning: Dynamic In-Context Editing for Long-Text Understanding. Weizhi Fei, Xueyan Niu, Guoqing Xie, Yanhua Zhang, Bo Bai, Lei Deng, Wei Han. Arxiv 2024.

22. FoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answering. Tianchi Cai, Zhiwen Tan, Xierui Song, Tao Sun, Jiyan Jiang, Yunqi Xu, Yinger Zhang, Jinjie Gu. Arxiv 2024.

23. Can Few-shot Work in Long-Context? Recycling the Context to Generate Demonstrations. Arie Cattan, Alon Jacovi, Alex Fabrikant, Jonathan Herzig, Roee Aharoni, Hannah Rashkin, Dror Marcus, Avinatan Hassidim, Yossi Matias, Idan Szpektor, Avi Caciularu. Arxiv 2024.

24. LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs. Ziyan Jiang, Xueguang Ma, Wenhu Chen. Arxiv 2024.        

25. Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning. Brandon Huang, Chancharik Mitra, Assaf Arbelle, Leonid Karlinsky, Trevor Darrell, Roei Herzig. Arxiv 2024.

26. From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data. Zheyang Xiong, Vasilis Papageorgiou, Kangwook Lee, Dimitris Papailiopoulos. Arxiv 2024.

27. Memory3: Language Modeling with Explicit Memory. Hongkang Yang, Zehao Lin, Wenjin Wang, Hao Wu, Zhiyu Li, Bo Tang, Wenqiang Wei, Jinbo Wang, Zeyun Tang, Shichao Song, Chenyang Xi, Yu Yu, Kai Chen, Feiyu Xiong, Linpeng Tang, Weinan E. Arxiv 2024.

28. Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting. Zilong Wang, Zifeng Wang, Long Le, Huaixiu Steven Zheng, Swaroop Mishra, Vincent Perot, Yuwei Zhang, Anush Mattapalli, Ankur Taly, Jingbo Shang, Chen-Yu Lee, Tomas Pfister. Arxiv 2024.

29. Retrieve, Summarize, Plan: Advancing Multi-hop Question Answering with an Iterative Approach. Zhouyu Jiang, Mengshu Sun, Lei Liang, Zhiqiang Zhang. Arxiv 2024.

30. R^2AG: Incorporating Retrieval Information into Retrieval Augmented Generation. Fuda Ye, Shuangyin Li, Yongqi Zhang, Lei Chen. Arxiv 2024.

31. Making Long-Context Language Models Better Multi-Hop Reasoners. Yanyang Li, Shuo Liang, Michael R. Lyu, Liwei Wang. ACL 2024.

32. Large Language Models Know What Makes Exemplary Contexts. Quanyu Long, Jianda Chen, Wenya Wang, Sinno Jialin Pan. Arxiv 2024.

33. RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation. Dongyu Ru, Lin Qiu, Xiangkun Hu, Tianhang Zhang, Peng Shi, Shuaichen Chang, Cheng Jiayang, Cunxiang Wang, Shichao Sun, Huanyu Li, Zizhao Zhang, Binjie Wang, Jiarong Jiang, Tong He, Zhiguo Wang, Pengfei Liu, Yue Zhang, Zheng Zhang. Arxiv 2024.

34. Writing in the Margins: Better Inference Pattern for Long Context Retrieval. Melisa Russak, Umar Jamil, Christopher Bryant, Kiran Kamble, Axel Magnuson, Mateusz Russak, Waseem AlShikh. Arxiv 2024.

35. MemLong: Memory-Augmented Retrieval for Long Text Modeling. Weijie Liu, Zecheng Tang, Juntao Li, Kehai Chen, Min Zhang. Arxiv 2024.

36. In Defense of RAG in the Era of Long-Context Language Models. Tan Yu, Anbang Xu, Rama Akkiraju. Arxiv 2024.

37. MemoRAG: Moving towards Next-Gen RAG Via Memory-Inspired Knowledge Discovery. Hongjin Qian, Peitian Zhang, Zheng Liu, Kelong Mao, Zhicheng Dou. Arxiv 2024.

38. You Only Use Reactive Attention Slice For Long Context Retrieval. Yun Joon Soh, Hanxian Huang, Yuandong Tian, Jishen Zhao. Arxiv 2024.

39. SMART-RAG: Selection using Determinantal Matrices for Augmented Retrieval. Jiatao Li, Xinyu Hu, Xiaojun Wan. Arxiv 2024.

40. Lighter And Better: Towards Flexible Context Adaptation For Retrieval Augmented Generation. Zheng Liu, Chenyuan Wu, Ninglu Shao, Shitao Xiao, Chaozhuo Li, Defu Lian. CIKM 2024.

41. Bridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding. Yanming Liu, Xinyue Peng, Jiannan Cao, Shi Bo, Yanxin Shen, Xuhong Zhang, Sheng Cheng, Xun Wang, Jianwei Yin, Tianyu Du. Arxiv 2024.

42. ALR2: A Retrieve-then-Reason Framework for Long-context Question Answering. Huayang Li, Pat Verga, Priyanka Sen, Bowen Yang, Vijay Viswanathan, Patrick Lewis, Taro Watanabe, Yixuan Su. Arxiv 2024.

43. Inference Scaling for Long-Context Retrieval Augmented Generation. Zhenrui Yue, Honglei Zhuang, Aijun Bai, Kai Hui, Rolf Jagerman, Hansi Zeng, Zhen Qin, Dong Wang, Xuanhui Wang, Michael Bendersky. Arxiv 2024.

44. GARLIC: LLM-Guided Dynamic Progress Control with Hierarchical Weighted Graph for Long Document QA. Xinyu Wang, Yanzheng Xiang, Lin Gui, Yulan He. Arxiv 2024.

45. Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG. Bowen Jin, Jinsung Yoon, Jiawei Han, Sercan O. Arik. Arxiv 2024.

46. Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models. Fei Wang, Xingchen Wan, Ruoxi Sun, Jiefeng Chen, Sercan Ö. Arık. Arxiv 2024.

47. SEGMENT+: Long Text Processing with Short-Context Language Models. Wei Shi, Shuang Li, Kerun Yu, Jinglei Chen, Zujie Liang, Xinhui Wu, Yuxi Qian, Feng Wei, Bo Zheng, Jiaqing Liang, Jiangjie Chen, Yanghua Xiao. Arxiv 2024.

48. Graph of Records: Boosting Retrieval Augmented Generation for Long-context Summarization with Graphs. Haozhen Zhang, Tao Feng, Jiaxuan You. Arxiv 2024.

49. ChuLo: Chunk-Level Key Information Representation for Long Document Processing. Yan Li, Caren Han, Yue Dai, Feiqi Cao. Arxiv 2024.

50. TurboRAG: Accelerating Retrieval-Augmented Generation with Precomputed KV Caches for Chunked Text. Songshuo Lu, Hua Wang, Yutian Rong, Zhi Chen, Yaohua Tang. Arxiv 2024.

51. LLM×MapReduce: Simplified Long-Sequence Processing using Large Language Models. Zihan Zhou, Chong Li, Xinyi Chen, Shuo Wang, Yu Chao, Zhili Li, Haoyu Wang, Rongqiao An, Qi Shi, Zhixing Tan, Xu Han, Xiaodong Shi, Zhiyuan Liu, Maosong Sun. Arxiv 2024.

52. Enhancing Long Context Performance in LLMs Through Inner Loop Query Mechanism. Yimin Tang, Yurong Xu, Ning Yan, Masood Mortazavi. NeurIPS 2024.

53. LongRAG: A Dual-Perspective Retrieval-Augmented Generation Paradigm for Long-Context Question Answering. Qingfei Zhao, Ruobing Wang, Yukuo Cen, Daren Zha, Shicheng Tan, Yuxiao Dong, Jie Tang. Arxiv 2024.

54. Reducing Distraction in Long-Context Language Models by Focused Learning. Zijun Wu, Bingyuan Liu, Ran Yan, Lei Chen, Thomas Delteil. Arxiv 2024.

55. Sliding Windows Are Not the End: Exploring Full Ranking with Long-Context Large Language Models. Wenhan Liu, Xinyu Ma, Yutao Zhu, Ziliang Zhao, Shuaiqiang Wang, Dawei Yin, Zhicheng Dou. Arxiv 2024.

56. Revisiting In-Context Learning with Long Context Language Models. Jinheon Baek, Sun Jae Lee, Prakhar Gupta, Geunseob (GS)Oh, Siddharth Dalmia, Prateek Kolhar. Arxiv 2024.

57. Eliciting In-context Retrieval and Reasoning for Long-context Large Language Models. Yifu Qiu, Varun Embar, Yizhe Zhang, Navdeep Jaitly, Shay B. Cohen, Benjamin Han. Arxiv 2024.

58. CacheFocus: Dynamic Cache Re-Positioning for Efficient Retrieval-Augmented Generation. Kun-Hui Lee, Eunhwan Park, Donghoon Han, Seung-Hoon Na. Arxiv 2025.

59. Lost in the Passage: Passage-level In-context Learning Does Not Necessarily Need a "Passage". Hao Sun, Chenming Tang, Gengyang Li, Yunfang Wu. Arxiv 2025.

60. MuDAF: Long-Context Multi-Document Attention Focusing through Contrastive Learning on Attention Heads. Weihao Liu, Ning Wu, Shiping Yang, Wenbiao Ding, Shining Liang, Ming Gong, Dongmei Zhang. Arxiv 2025.

61. Cache-Craft: Managing Chunk-Caches for Efficient Retrieval-Augmented Generation. Shubham Agarwal, Sai Sundaresan, Subrata Mitra, Debabrata Mahapatra, Archit Gupta, Rounak Sharma, Nirmal Joshua Kapu, Tong Yu, Shiv Saini. SIGMOD 2025.

62. OkraLong: A Flexible Retrieval-Augmented Framework for Long-Text Query Processing. Yulong Hui, Yihao Liu, Yao Lu, Huanchen Zhang. Arxiv 2025.

63. Beyond RAG: Task-Aware KV Cache Compression for Comprehensive Knowledge Reasoning. Giulio Corallo, Orion Weller, Fabio Petroni, Paolo Papotti. Arxiv 2025.

64. Efficient Many-Shot In-Context Learning with Dynamic Block-Sparse Attention. Emily Xiao, Chin-Jou Li, Yilin Zhang, Graham Neubig, Amanda Bertsch. Arxiv 2025.

65. Long Context Modeling with Ranked Memory-Augmented Retrieval. Ghadir Alselwi, Hao Xue, Shoaib Jameel, Basem Suleiman, Flora D. Salim, Imran Razzak. Arxiv 2025.

66. Tuning LLMs by RAG Principles: Towards LLM-native Memory. Jiale Wei, Shuchi Wu, Ruochen Liu, Xiang Ying, Jingbo Shang, Fangbo Tao. Arxiv 2025.

67. ReaRAG: Knowledge-guided Reasoning Enhances Factuality of Large Reasoning Models with Iterative Retrieval Augmented Generation. Zhicheng Lee, Shulin Cao, Jinxin Liu, Jiajie Zhang, Weichuan Liu, Xiaoyin Che, Lei Hou, Juanzi Li. Arxiv 2025.

68. Focus Directions Make Your Language Models Pay More Attention to Relevant Contexts. Youxiang Zhu, Ruochen Li, Danqing Wang, Daniel Haehn, Xiaohui Liang. Arxiv 2025.

69. FReM: A Flexible Reasoning Mechanism for Balancing Quick and Slow Thinking in Long-Context Question Answering. Zhengyi Zhao, Shubo Zhang, Zezhong Wang, Bin Liang, Binyang Li, Kam-Fai Wong. Arxiv 2025.

70. Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models. Boheng Sheng, Jiacheng Yao, Meicong Zhang, Guoxiu He. Arxiv 2025.

71. Conflict-Aware Soft Prompting for Retrieval-Augmented Generation. Eunseong Choi, June Park, Hyeri Lee, Jongwuk Lee. EMNLP 2025.

8. Agent

1. LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration. Jun Zhao, Can Zu, Hao Xu, Yi Lu, Wei He, Yiwen Ding, Tao Gui, Qi Zhang, Xuanjing Huang. Arxiv 2024.

2. A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis. Izzeddin Gur, Hiroki Furuta, Austin V Huang, Mustafa Safdari, Yutaka Matsuo, Douglas Eck, Aleksandra Faust. ICLR 2024 Oral.

3. PEARL: Prompting Large Language Models to Plan and Execute Actions Over Long Documents. Simeng Sun, Yang Liu, Shuohang Wang, Dan Iter, Chenguang Zhu, Mohit Iyyer. EACL 2024.

4. AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents. Jake Grigsby, Linxi Fan, Yuke Zhu. ICLR 2024 Spotlight.        

5. Chain of Agents: Large Language Models Collaborating on Long-Context Tasks. Yusen Zhang, Ruoxi Sun, Yanfei Chen, Tomas Pfister, Rui Zhang, Sercan Ö. Arik. Arxiv 2024.

6. GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models. Shilong Li, Yancheng He, Hangyu Guo, Xingyuan Bu, Ge Bai, Jie Liu, Jiaheng Liu, Xingwei Qu, Yangguang Li, Wanli Ouyang, Wenbo Su, Bo Zheng. Arxiv 2024.

7. Synergistic Multi-Agent Framework with Trajectory Learning for Knowledge-Intensive Tasks. Shengbin Yue, Siyuan Wang, Wei Chen, Xuanjing Huang, Zhongyu Wei. Arxiv 2024.

8. Optimus-1: Hybrid Multimodal Memory Empowered Agents Excel in Long-Horizon Tasks. Zaijing Li, Yuquan Xie, Rui Shao, Gongwei Chen, Dongmei Jiang, Liqiang Nie. Arxiv 2024.        

9. Compress

9.1 Context

1. Adapting Language Models to Compress Contexts. Alexis Chevalier, Alexander Wettig, Anirudh Ajith, Danqi Chen. Arxiv 2023.

2. Compressing Context to Enhance Inference Efficiency of Large Language Models. Yucheng Li, Bo Dong, Chenghua Lin, Frank Guerin. Arxiv 2023.

3. LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models. Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, Yuqing Yang, Lili Qiu. Arxiv 2023.

4. LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression. Huiqiang Jiang, Qianhui Wu, Xufang Luo, Dongsheng Li, Chin-Yew Lin, Yuqing Yang, Lili Qiu. Arxiv 2023.

5. System 2 Attention (is something you might need too). Jason Weston, Sainbayar Sukhbaatar. Arxiv 2023.

6. Soaring from 4K to 400K: Extending LLM's Context with Activation Beacon. Peitian Zhang, Zheng Liu, Shitao Xiao, Ninglu Shao, Qiwei Ye, Zhicheng Dou. Arxiv 2024.

7. Flexibly Scaling Large Language Models Contexts Through Extensible Tokenization. Ninglu Shao, Shitao Xiao, Zheng Liu, Peitian Zhang. Arxiv 2024.

8. Say More with Less: Understanding Prompt Learning Behaviors through Gist Compression. Xinze Li, Zhenghao Liu, Chenyan Xiong, Shi Yu, Yukun Yan, Shuo Wang, Ge Yu. Arxiv 2024.

9. Learning to Compress Prompt in Natural Language Formats. Yu-Neng Chuang, Tianwei Xing, Chia-Yuan Chang, Zirui Liu, Xun Chen, Xia Hu. Arxiv 2024.

10. Dynamic Memory Compression: Retrofitting LLMs for Accelerated Inference. Piotr Nawrot, Adrian Łańcucki, Marcin Chochowski, David Tarjan, Edoardo M. Ponti. Arxiv 2024.

11. LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression. Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Menglin Xia, Xufang Luo, Jue Zhang, Qingwei Lin, Victor Rühle, Yuqing Yang, Chin-Yew Lin, H. Vicky Zhao, Lili Qiu, Dongmei Zhang. Arxiv 2024.

12. PCToolkit: A Unified Plug-and-Play Prompt Compression Toolkit of Large Language Models. Jinyi Li, Yihuai Lan, Lei Wang, Hao Wang. Arxiv 2024.

13. Compressed Context Memory for Online Language Model Interaction. Jang-Hyun Kim, Junyoung Yeom, Sangdoo Yun, Hyun Oh Song. ICLR 2024.

14. PROMPT-SAW: Leveraging Relation-Aware Graphs for Textual Prompt Compression. Muhammad Asif Ali, Zhengping Li, Shu Yang, Keyuan Cheng, Yang Cao, Tianhao Huang, Lijie Hu, Lu Yu, Di Wang. Arxiv 2024.

15. Training LLMs over Neurally Compressed Text. Brian Lester, Jaehoon Lee, Alex Alemi, Jeffrey Pennington, Adam Roberts, Jascha Sohl-Dickstein, Noah Constant. Arxiv 2024.

16. Rethinking Kullback-Leibler Divergence in Knowledge Distillation for Large Language Models. Taiqiang Wu, Chaofan Tao, Jiahao Wang, Zhe Zhao, Ngai Wong. Arxiv 2024.

17. Adapting LLMs for Efficient Context Processing through Soft Prompt Compression. Cangqing Wang, Yutian Yang, Ruisi Li, Dan Sun, Ruicong Cai, Yuzhu Zhang, Chengqian Fu, Lillian Floyd. Arxiv 2024.

18. Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs. Suyu Ge, Yunan Zhang, Liyuan Liu, Minjia Zhang, Jiawei Han, Jianfeng Gao. ICLR 2024 Oral.

19. LLoCO: Learning Long Contexts Offline. Sijun Tan, Xiuyu Li, Shishir Patil, Ziyang Wu, Tianjun Zhang, Kurt Keutzer, Joseph E. Gonzalez, Raluca Ada Popa. Arxiv 2024.

20. In-Context Learning State Vector with Inner and Momentum Optimization. Dongfang Li, Zhenyu Liu, Xinshuo Hu, Zetian Sun, Baotian Hu, Min Zhang. Arxiv 2024.

21. Compressing Long Context for Enhancing RAG with AMR-based Concept Distillation. Kaize Shi, Xueyao Sun, Qing Li, Guandong Xu. Arxiv 2024.

22. Improving Long Text Understanding with Knowledge Distilled from Summarization Model. Yan Liu, Yazheng Yang, Xiaokang Chen. Arxiv 2024.

23. OpenBA-V2: Reaching 77.3% High Compression Ratio with Fast Multi-Stage Pruning. Dan Qiao, Yi Su, Pinzheng Wang, Jing Ye, Wenjing Xie, Yuechi Zhou, Yuyang Ding, Zecheng Tang, Jikai Wang, Yixin Ji, Yue Wang, Pei Guo, Zechen Sun, Zikang Zhang, Juntao Li, Pingfu Chao, Wenliang Chen, Guohong Fu, Guodong Zhou, Qiaoming Zhu, Min Zhang. Arxiv 2024.

24. Imagination Augmented Generation: Learning to Imagine Richer Context for Question Answering over Large Language Models. Huanxuan Liao, Shizhu He, Yao Xu, Yuanzhe Zhang, Kang Liu, Shengping Liu, Jun Zhao. Arxiv 2024.

25. xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token. Xin Cheng, Xun Wang, Xingxing Zhang, Tao Ge, Si-Qing Chen, Furu Wei, Huishuai Zhang, Dongyan Zhao. Arxiv 2024.

26. SelfCP: Compressing Long Prompt to 1/12 Using the Frozen Large Language Model Itself. Jun Gao. Arxiv 2024.

27. Compressing Lengthy Context With UltraGist. Peitian Zhang, Zheng Liu, Shitao Xiao, Ninglu Shao, Qiwei Ye, Zhicheng Dou. Arxiv 2024.

28. XL3M: A Training-free Framework for LLM Length Extension Based on Segment-wise Inference. Shengnan Wang, Youhui Bai, Lin Zhang, Pingyi Zhou, Shixiong Zhao, Gong Zhang, Sen Wang, Renhai Chen, Hua Xu, Hongwei Sun. Arxiv 2024.

29. In-context Autoencoder for Context Compression in a Large Language Model. Tao Ge, Hu Jing, Lei Wang, Xun Wang, Si-Qing Chen, Furu Wei. ICLR 2024.

30. Retaining Key Information under High Compression Ratios: Query-Guided Compressor for LLMs. Zhiwei Cao, Qian Cao, Yu Lu, Ningxin Peng, Luyang Huang, Shanbo Cheng, Jinsong Su. Arxiv 2024.

31. Recurrent Context Compression: Efficiently Expanding the Context Window of LLM. Chensen Huang, Guibo Zhu, Xuepeng Wang, Yifei Luo, Guojing Ge, Haoran Chen, Dong Yi, Jinqiao Wang. Arxiv 2024.

32. LoCoCo: Dropping In Convolutions for Long Context Compression. Ruisi Cai, Yuandong Tian, Zhangyang Wang, Beidi Chen. Arxiv 2024.

33. InstructCMP: Length Control in Sentence Compression through Instruction-based Large Language Models. Juseon-Do, Jingun Kwon, Hidetaka Kamigaito, Manabu Okumura. Arxiv 2024.

34. In-Context Former: Lightning-fast Compressing Context for Large Language Model. Xiangfeng Wang, Zaiyi Chen, Zheyong Xie, Tong Xu, Yongyi He, Enhong Chen. Arxiv 2024.

35. UIO-LLMs: Unbiased Incremental Optimization for Long-Context LLMs. Wenhao Li, Mingbao Lin, Yunshan Zhong, Shuicheng Yan, Rongrong Ji. Arxiv 2024.

36. PromptIntern: Saving Inference Costs by Internalizing Recurrent Prompt during Large Language Model Fine-tuning. Jiaru Zou, Mengyu Zhou, Tao Li, Shi Han, Dongmei Zhang. Arxiv 2024.

37. Concise and Precise Context Compression for Tool-Using Language Models. Yang Xu, Yunlong Feng, Honglin Mu, Yutai Hou, Yitong Li, Xinghao Wang, Wanjun Zhong, Zhongyang Li, Dandan Tu, Qingfu Zhu, Min Zhang, Wanxiang Che. Arxiv 2024.

38. Context Embeddings for Efficient Answer Generation in RAG. David Rau, Shuai Wang, Hervé Déjean, Stéphane Clinchant. Arxiv 2024.

39. Characterizing Prompt Compression Methods for Long Context Inference. Siddharth Jha, Lutfi Eren Erdogan, Sehoon Kim, Kurt Keutzer, Amir Gholami. Arxiv 2024.

40. AgentOCR: Reimagining Agent History via Optical Self-Compression. Lang Feng, Fuchao Yang, Feng Chen, Xin Cheng, Haiyang Xu, Zhenglin Wan, Ming Yan, Bo An. Arxiv 2026.

41. Fundamental Limits of Prompt Compression: A Rate-Distortion Framework for Black-Box Language Models. Adway Girish, Alliot Nagle, Marco Bondaschi, Michael Gastpar, Ashok Vardhan Makkuva, Hyeji Kim. Arxiv 2024.

42. QUITO: Accelerating Long-Context Reasoning through Query-Guided Context Compression. Wenshan Wang, Yihang Wang, Yixing Fan, Huaming Liao, Jiafeng Guo. Arxiv 2024.

43. SentenceVAE: Faster, Longer and More Accurate Inference with Next-sentence Prediction for Large Language Models. Hongjun An, Yifan Chen, Xiaozhen Qiao, Zhe Sun, Xuelong Li. Arxiv 2024.

44. QUITO-X: An Information Bottleneck-based Compression Algorithm with Cross-Attention. Yihang Wang, Xu Huang, Bowen Tian, Yixing Fan, Jiafeng Guo. Arxiv 2024.

45. AdaComp: Extractive Context Compression with Adaptive Predictor for Retrieval-Augmented Large Language Models. Qianchi Zhang, Hainan Zhang, Liang Pang, Hongwei Zheng, Zhiming Zheng. Arxiv 2024.

46. Prompt Compression with Context-Aware Sentence Encoding for Fast and Improved LLM Inference. Barys Liskavets, Maxim Ushakov, Shuvendu Roy, Mark Klibanov, Ali Etemad, Shane Luke. Arxiv 2024.

47. Familiarity-aware Evidence Compression for Retrieval Augmented Generation. Dongwon Jung, Qin Liu, Tenghao Huang, Ben Zhou, Muhao Chen. Arxiv 2024.

48. TACO-RL: Task Aware Prompt Compression Optimization with Reinforcement Learning. Shivam Shandilya, Menglin Xia, Supriyo Ghosh, Huiqiang Jiang, Jue Zhang, Qianhui Wu, Victor Rühle. Arxiv 2024.

49. Parse Trees Guided LLM Prompt Compression. Wenhao Mao, Chengbin Hou, Tianyu Zhang, Xinyu Lin, Ke Tang, Hairong Lv. Arxiv 2024.

50. FineZip: Pushing the Limits of Large Language Models for Practical Lossless Text Compression. Fazal Mittu, Yihuan Bu, Akshat Gupta, Ashok Devireddy, Alp Eren Ozdarendeli, Anant Singh, Gopala Anumanchipalli. Arxiv 2024.

51. Perception Compressor:A training-free prompt compression method in long context scenarios. Jiwei Tang, Jin Xu, Tingwei Lu, Hai Lin, Yiming Zhao, Hai-Tao Zheng. Arxiv 2024.

52. From Reading to Compressing: Exploring the Multi-document Reader for Prompt Compression. Eunseong Choi, Sunkyung Lee, Minjin Choi, June Park, Jongwuk Lee. EMNLP 2024.

53. Selection-p: Self-Supervised Task-Agnostic Prompt Compression for Faithfulness and Transferability. Tsz Ting Chung, Leyang Cui, Lemao Liu, Xinting Huang, Shuming Shi, Dit-Yan Yeung. EMNLP 2024.

54. Style-Compress: An LLM-Based Prompt Compression Framework Considering Task-Specific Styles. Xiao Pu, Tianxing He, Xiaojun Wan. EMNLP 2024.

55. SpeechPrune: Context-aware Token Pruning for Speech Information Retrieval. Yueqian Lin, Yuzhe Fu, Jingyang Zhang, Yudong Liu, Jianyi Zhang, Jingwei Sun, Hai "Helen" Li, Yiran Chen. Arxiv 2024.

56. FTP: A Fine-grained Token-wise Pruner for Large Language Models via Token Routing. Zekai Li, Jintu Zheng, Ji Liu, Han Liu, Haowei Zhu, Zeping Li, Fuwei Yang, Haiduo Huang, Jinzhang Peng, Dong Li, Lu Tian, Emad Barsoum. Arxiv 2024.

57. CSR:Achieving 1 Bit Key-Value Cache via Sparse Representation. Hongxuan Zhang, Yao Zhao, Jiaqi Zheng, Chenyi Zhuang, Jinjie Gu, Guihai Chen. AAAI 2025.

58. EXIT: Context-Aware Extractive Compression for Enhancing Retrieval-Augmented Generation. Taeho Hwang, Sukmin Cho, Soyeong Jeong, Hoyun Song, SeungYoon Han, Jong C. Park. Arxiv 2024.

59. A Silver Bullet or a Compromise for Full Attention? A Comprehensive Study of Gist Token-based Context Compression. Chenlong Deng, Zhisong Zhang, Kelong Mao, Shuaiyi Li, Xinting Huang, Dong Yu, Zhicheng Dou. Arxiv 2024.

60. Layer- and Timestep-Adaptive Differentiable Token Compression Ratios for Efficient Diffusion Transformers. Haoran You, Connelly Barnes, Yuqian Zhou, Yan Kang, Zhenbang Du, Wei Zhou, Lingzhi Zhang, Yotam Nitzan, Xiaoyang Liu, Zhe Lin, Eli Shechtman, Sohrab Amirghodsi, Yingyan Celine Lin. Arxiv 2024.

61. Efficient Prompt Compression with Evaluator Heads for Long-Context Transformer Inference. Weizhi Fei, Xueyan Niu, Guoqing Xie, Yingqing Liu, Bo Bai, Wei Han. Arxiv 2025.

62. PISCO: Pretty Simple Compression for Retrieval-Augmented Generation. Maxime Louis, Hervé Déjean, Stéphane Clinchant. Arxiv 2025.

63. Provence: efficient and robust context pruning for retrieval-augmented generation. Nadezhda Chirkova, Thibault Formal, Vassilina Nikoulina, Stéphane Clinchant. ICLR 2025.

64. Knowing When to Stop: Dynamic Context Cutoff for Large Language Models. Roy Xie, Junlin Wang, Paul Rosu, Chunyuan Deng, Bolun Sun, Zihao Lin, Bhuwan Dhingra. Arxiv 2025.        

65. LCIRC: A Recurrent Compression Approach for Efficient Long-form Context and Query Dependent Modeling in LLMs. Sumin An, Junyoung Sung, Wonpyo Park, Chanjun Park, Paul Hongsuck Seo. NAACL 2025.

66. DAST: Context-Aware Compression in LLMs via Dynamic Allocation of Soft Tokens. Shaoshen Chen, Yangning Li, Zishan Xu, Yinghui Li, Xin Su, Zifei Shan, Hai-tao Zheng. Arxiv 2025.

67. Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?. Zichen Wen, Yifeng Gao, Weijia Li, Conghui He, Linfeng Zhang. Arxiv 2025.

68. Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity. Yuri Kuratov, Mikhail Arkhipov, Aydar Bulatov, Mikhail Burtsev. Arxiv 2025.

69. FCoT-VL:Advancing Text-oriented Large Vision-Language Models with Efficient Visual Token Compression. Jianjian Li, Junquan Fan, Feng Tang, Gang Huang, Shitao Zhu, Songlin Liu, Nian Xie, Wulong Liu, Yong Liao. Arxiv 2025.

70. DivPrune: Diversity-based Visual Token Pruning for Large Multimodal Models. Saeed Ranjbar Alvar, Gursimran Singh, Mohammad Akbari, Yong Zhang. Arxiv 2025.

71. EFPC: Towards Efficient and Flexible Prompt Compression. Yun-Hao Cao, Yangsong Wang, Shuzheng Hao, Zhenxing Li, Chengjun Zhan, Sichao Liu, Yi-Qi Hu. Arxiv 2025.

72. AttentionRAG: Attention-Guided Context Pruning in Retrieval-Augmented Generation. Yixiong Fang, Tianran Sun, Yuling Shi, Xiaodong Gu. Arxiv 2025.

73. Limits of KV Cache Compression for Tensor Attention based Autoregressive Transformers. Yifang Chen, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song, Yu Tian. Arxiv 2025.

74. Hybrid-Level Instruction Injection for Video Token Compression in Multi-modal Large Language Models. Zhihang Liu, Chen-Wei Xie, Pandeng Li, Liming Zhao, Longxiang Tang, Yun Zheng, Chuanbin Liu, Hongtao Xie. CVPR 2025.

75. Token Dynamics: Towards Efficient and Dynamic Video Token Representation for Video Large Language Models. Haichao Zhang, Zhuowei Li, Dimitris Metaxas, Yun Fu. Arxiv 2025.

76. Understanding and Improving Information Preservation in Prompt Compression for LLMs. Weronika Łajewska, Momchil Hardalov, Laura Aina, Neha Anna John, Hang Su, Lluís Màrquezu. Arxiv 2025.

77. Fwd2Bot: LVLM Visual Token Compression with Double Forward Bottleneck. Adrian Bulat, Yassine Ouali, Georgios Tzimiropoulos. Arxiv 2025.

78. Efficient Dynamic Clustering-Based Document Compression for Retrieval-Augmented-Generation. Weitao Li, Kaiming Liu, Xiangyu Zhang, Xuanyu Lei, Weizhi Ma, Yang Liu. Arxiv 2025.

79. Saliency-driven Dynamic Token Pruning for Large Language Models. Yao Tao, Yehui Tang, Yun Wang, Mingjian Zhu, Hailin Hu, Yunhe Wang. Arxiv 2025.

80. Dynamic Compressing Prompts for Efficient Inference of Large Language Models. Jinwu Hu, Wei Zhang, Yufeng Wang, Yu Hu, Bin Xiao, Mingkui Tan, Qing Du. Arxiv 2025.

81. ACoRN: Noise-Robust Abstractive Compression in Retrieval-Augmented Language Models. Singon Kim, Gunho Jung, Seong-Whan Lee. Arxiv 2025.

82. MOOSComp: Improving Lightweight Long-Context Compressor via Mitigating Over-Smoothing and Incorporating Outlier Scores. Fengwei Zhou, Jiafei Song, Wenjin Jason Li, Gengjian Xue, Zhikang Zhao, Yichao Lu, Bailin Na. Arxiv 2025.

83. Token Sequence Compression for Efficient Multimodal Computing. Yasmine Omri, Parth Shroff, Thierry Tambe. Arxiv 2025.

84. An Empirical Study on Prompt Compression for Large Language Models. Zheng Zhang, Jinyi Li, Yihuai Lan, Xiang Wang, Hao Wang. Arxiv 2025.

85. Video Compression Commander: Plug-and-Play Inference Acceleration for Video Large Language Models. Xuyang Liu, Yiyu Wang, Junpeng Ma, Linfeng Zhang. Arxiv 2025.

86. Beyond Hard and Soft: Hybrid Context Compression for Balancing Local and Global Information Retention. Huanxuan Liao, Wen Hu, Yao Xu, Shizhu He, Jun Zhao, Kang Liu. Arxiv 2025.

87. QwenLong-CPRS: Towards ∞-LLMs with Dynamic Context Optimization. Weizhou Shen, Chenliang Li, Fanqi Wan, Shengyi Liao, Shaopeng Lai, Bo Zhang, Yingcheng Shi, Yuning Wu, Gang Fu, Zhansheng Li, Bin Yang, Ji Zhang, Fei Huang, Jingren Zhou, Ming Yan. Arxiv 2025.

88. Lossless Token Sequence Compression via Meta-Tokens. John Harvill, Ziwei Fan, Hao Wang, Yizhou Sun, Hao Ding, Luke Huan, Anoop Deoras. Arxiv 2025.

89. Sentinel: Attention Probing of Proxy Models for LLM Context Compression with an Understanding Perspective. Yong Zhang, Yanwen Huang, Ning Cheng, Yang Guo, Yun Zhu, Yanmeng Wang, Shaojun Wang, Jing Xiao. Arxiv 2025.

90. METok: Multi-Stage Event-based Token Compression for Efficient Long Video Understanding. Mengyue Wang, Shuo Chen, Kristian Kersting, Volker Tresp, Yunpu Ma. Arxiv 2025.

91. SecurityLingua: Efficient Defense of LLM Jailbreak Attacks via Security-Aware Prompt Compression. Yucheng Li, Surin Ahn, Huiqiang Jiang, Amir H. Abdi, Yuqing Yang, Lili Qiu. Arxiv 2025.

92. SARA: Selective and Adaptive Retrieval-augmented Generation with Context Compression. Yiqiao Jin, Kartik Sharma, Vineeth Rakesh, Yingtong Dou, Menghai Pan, Mahashweta Das, Srijan Kumar. Arxiv 2025.

93. DAC: A Dynamic Attention-aware Approach for Task-Agnostic Prompt Compression. Yi Zhao, Zuchao Li, Hai Zhao, Baoyuan Qi, Guoming Liu. ACL 2025.

94. ProCut: LLM Prompt Compression via Attribution Estimation. Zhentao Xu, Fengyi Li, Albert Chen, Xiaofeng Wang. Arxiv 2025.

95. DSPC: Dual-Stage Progressive Compression Framework for Efficient Long-Context Reasoning. Yaxin Gao, Yao Lu, Zongfei Zhang, Jiaqi Nie, Shanqing Yu, Qi Xuan. Arxiv 2025.

96. AttnComp: Attention-Guided Adaptive Context Compression for Retrieval-Augmented Generation. Lvzhou Luo, Yixuan Cao, Ping Luo. EMNLP 2025.

97. LongCodeZip: Compress Long Context for Code Language Models. Yuling Shi, Yichun Qian, Hongyu Zhang, Beijun Shen, Xiaodong Gu. ASE 2025.

98. ILRe: Intermediate Layer Retrieval for Context Compression in Causal Language Models. Manlai Liang, Mandi Liu, Jiangzhou Ji, Huaijun Li, Haobo Yang, Yaohan He, Jinlong Li. Arxiv 2025.

99. DeepSeek-OCR: Contexts Optical Compression. Haoran Wei, Yaofeng Sun, Yukun Li. Arxiv 2025.

100. See the Text: From Tokenization to Visual Reading. Ling Xing, Alex Jinpeng Wang, Rui Yan, Hongyu Qu, Zechao Li, Jinhui Tang. Arxiv 2025.

101. Simple Context Compression: Mean-Pooling and Multi-Ratio Training. Yair Feldman, Yoav Artzi. Arxiv 2025.

102. Context Cascade Compression: Exploring the Upper Limits of Text Compression. Fanfan Liu, Haibo Qiu. Arxiv 2025.

9.2 Model

1. DSFormer: Effective Compression of Text-Transformers by Dense-Sparse Weight Factorization. Rahul Chand, Yashoteja Prabhu, Pratyush Kumar. Arxiv 2023.

2. LLM-Pruner: On the Structural Pruning of Large Language Models. Xinyin Ma, Gongfan Fang, Xinchao Wang. NeurIPS 2023.

3. Compressing Large Language Models by Streamlining the Unimportant Layer. Xiaodong Chen, Yuxuan Hu, Jing Zhang. Arxiv 2024.

4. Feature-based Low-Rank Compression of Large Language Models via Bayesian Optimization. Yixin Ji, Yang Xiang, Juntao Li, Wei Chen, Zhongyi Liu, Kehai Chen, Min Zhang. ACL 2024.

5. Your Transformer is Secretly Linear. Anton Razzhigaev, Matvey Mikhalchuk, Elizaveta Goncharova, Nikolai Gerasimenko, Ivan Oseledets, Denis Dimitrov, Andrey Kuznetsov. Arxiv 2024.

6. Evaluating Zero-Shot Long-Context LLM Compression. Chenyu Wang, Yihan Wang. Arxiv 2024.

7. AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration. Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Wei-Ming Chen, Wei-Chen Wang, Guangxuan Xiao, Xingyu Dang, Chuang Gan, Song Han. MLSys 2024 Best Paper Award.

8. Merging Feed-Forward Sublayers for Compressed Transformers. Neha Verma, Kenton Murray, Kevin Duh. Arxiv 2025.

9. FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing. James Seale Smith, Chi-Heng Lin, Shikhar Tuli, Haris Jeelani, Shangqian Gao, Yilin Shen, Hongxia Jin, Yen-Chang Hsu. NAACL 2025.

10. TensorLLM: Tensorising Multi-Head Attention for Enhanced Reasoning and Compression in LLMs. Yuxuan Gu, Wuyang Zhou, Giorgos Iacovides, Danilo Mandic. Arxiv 2025.

11. You Only Prune Once: Designing Calibration-Free Model Compression With Policy Learning. Ayan Sengupta, Siddhant Chaudhary, Tanmoy Chakraborty. ICLR 2025.

12. Mamba-Shedder: Post-Transformer Compression for Efficient Selective Structured State Space Models. J. Pablo Muñoz, Jinjie Yuan, Nilesh Jain. NAACL 2025.

13. TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models. Makoto Shing, Kou Misaki, Han Bao, Sho Yokoi, Takuya Akiba. ICLR 2025.

14. AdaSVD: Adaptive Singular Value Decomposition for Large Language Models. Zhiteng Li, Mingyuan Xia, Jingyuan Zhang, Zheng Hui, Linghe Kong, Yulun Zhang, Xiaokang Yang. Arixv 2025.

15. Activation-Informed Merging of Large Language Models. Amin Heyrani Nobari, Kaveh Alimohammadi, Ali ArjomandBigdeli, Akash Srivastava, Faez Ahmed, Navid Azizan. Arixv 2025.

16. Adapt-Pruner: Adaptive Structural Pruning for Efficient Small Language Model Training. Boyao Wang, Rui Pan, Shizhe Diao, Xingyuan Pan, Jipeng Zhang, Renjie Pi, Tong Zhang. Arixv 2025.

17. QuEST: Stable Training of LLMs with 1-Bit Weights and Activations. Andrei Panferov, Jiale Chen, Soroush Tabesh, Roberto L. Castro, Mahdi Nikdan, Dan Alistarh. Arixv 2025.

18. DarwinLM: Evolutionary Structured Pruning of Large Language Models. Shengkun Tang, Oliver Sieberling, Eldar Kurtic, Zhiqiang Shen, Dan Alistarh. Arixv 2025.

19. Hyper Compressed Fine-Tuning of Large Foundation Models with Quantum Inspired Adapters. Snehal Raj, Brian Coyle. Arixv 2025.

20. Contextual Compression Encoding for Large Language Models: A Novel Framework for Multi-Layered Parameter Space Pruning. Barnaby Schmitt, Alistair Grosvenor, Matthias Cunningham, Clementine Walsh, Julius Pembrokeshire, Jonathan Teel. Arixv 2025.

21. Forget the Data and Fine-Tuning! Just Fold the Network to Compress. Dong Wang, Haris Šikić, Lothar Thiele, Olga Saukh. ICLR 2025.

22. NestQuant: Nested Lattice Quantization for Matrix Products and LLMs. Semyon Savkin, Eitan Porat, Or Ordentlich, Yury Polyanskiy. Arixv 2025.

23. 1bit-Merging: Dynamic Quantized Merging for Large Language Models. Shuqi Liu, Han Wu, Bowei He, Zehua Liu, Xiongwei Han, Mingxuan Yuan, Linqi Song. Arixv 2025.

24. Every Expert Matters: Towards Effective Knowledge Distillation for Mixture-of-Experts Language Models. Gyeongman Kim, Gyouk Chu, Eunho Yang. Arixv 2025.

25. NestQuant: Nested Lattice Quantization for Matrix Products and LLMs. Semyon Savkin, Eitan Porat, Or Ordentlich, Yury Polyanskiy. Arixv 2025.

26. When Compression Meets Model Compression: Memory-Efficient Double Compression for Large Language Models. Weilan Wang, Yu Mao, Dongdong Tang, Hongchao Du, Nan Guan, Chun Jason Xue. Arixv 2025.

27. Optimizing Singular Spectrum for Large Language Model Compression. Dengjie Li, Tiancheng Shen, Yao Zhou, Baisong Yang, Zhongying Liu, Masheng Yang, Bernard Ghanem, Yibo Yang, Yujie Zhong, Ming-Hsuan Yang. Arixv 2025.

28. Rotate, Clip, and Partition: Towards W2A4KV4 Quantization by Integrating Rotation and Learnable Non-uniform Quantizer. Euntae Choi, Sumin Song, Woosang Lim, Sungjoo Yoo. Arixv 2025.

29. Delta Decompression for MoE-based LLMs Compression. Hao Gu, Wei Li, Lujun Li, Qiyuan Zhu, Mark Lee, Shengjie Sun, Wei Xue, Yike Guo. Arxiv 2025.

30. The Lottery LLM Hypothesis, Rethinking What Abilities Should LLM Compression Preserve?. Zhenheng Tang, Xiang Liu, Qian Wang, Peijie Dong, Bingsheng He, Xiaowen Chu, Bo Li. ICLR 2025.

31. Compressing Language Models for Specialized Domains. Miles Williams, George Chrysostomou, Vitor Jeronymo, Nikolaos Aletras. Arxiv 2025.

32. Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners. Daniele Paliotta, Junxiong Wang, Matteo Pagliardini, Kevin Y. Li, Aviv Bick, J. Zico Kolter, Albert Gu, François Fleuret, Tri Dao. Arxiv 2025.

33. DeRS: Towards Extremely Efficient Upcycled Mixture-of-Experts Models. Yongqi Huang, Peng Ye, Chenyu Huang, Jianjian Cao, Lin Zhang, Baopu Li, Gang Yu, Tao Chen. CVPR 2025.

34. Efficiently Editing Mixture-of-Experts Models with Compressed Experts. Yifei He, Yang Liu, Chen Liang, Hany Hassan Awadalla. Arxiv 2025.

35. IDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model Pretraining. Yixiao Li, Xianzhi Du, Ajay Jaiswal, Tao Lei, Tuo Zhao, Chong Wang, Jianyu Wang. Arxiv 2025.

36. Position-Aware Depth Decay Decoding (D3): Boosting Large Language Model Inference Efficiency. Siqi Fan, Xuezhi Fang, Xingrun Xing, Peng Han, Shuo Shang, Yequan Wang. Arxiv 2025.

37. Towards Extreme Pruning of LLMs with Plug-and-Play Mixed Sparsity. Chi Xu, Gefei Zhang, Yantong Zhu, Luca Benini, Guosheng Hu, Yawei Li, Zhihong Zhang. Arxiv 2025.

38. SVD-LLM V2: Optimizing Singular Value Truncation for Large Language Model Compression. Xin Wang, Samiul Alam, Zhongwei Wan, Hui Shen, Mi Zhang. NAACL 2025.

39. ClusComp: A Simple Paradigm for Model Compression and Efficient Finetuning. Baohao Liao, Christian Herold, Seyyed Hadi Hashemi, Stefan Vasilev, Shahram Khadivi, Christof Monz. Arxiv 2025.

40. Large Language Model Compression via the Nested Activation-Aware Decomposition. Jun Lu, Tianyi Xu, Bill Ding, David Li, Yu Kang. Arxiv 2025.

41. When Reasoning Meets Compression: Benchmarking Compressed Large Reasoning Models on Complex Reasoning Tasks. Nan Zhang, Yusen Zhang, Prasenjit Mitra, Rui Zhang. Arxiv 2025.

42. Compression Laws for Large Language Models. Ayan Sengupta, Siddhant Chaudhary, Tanmoy Chakraborty. Arxiv 2025.

43. Thanos: A Block-wise Pruning Algorithm for Efficient Large Language Model Compression. Ivan Ilin, Peter Richtarik. Arxiv 2025.

44. Efficient Hybrid Language Model Compression through Group-Aware SSM Pruning. Ali Taghibakhshi, Sharath Turuvekere Sreenivas, Saurav Muralidharan, Marcin Chochowski, Yashaswi Karnati, Raviraj Joshi, Ameya Sunil Mahabaleshwarkar, Zijia Chen, Yoshi Suhara, Oluwatobi Olabiyi, Daniel Korzekwa, Mostofa Patwary, Mohammad Shoeybi, Jan Kautz, Bryan Catanzaro, Ashwath Aithal, Nima Tajbakhsh, Pavlo Molchanov. Arxiv 2025.

45. 70% Size, 100% Accuracy: Lossless LLM Compression for Efficient GPU Inference via Dynamic-Length Float. Tianyi Zhang, Yang Sui, Shaochen Zhong, Vipin Chaudhary, Xia Hu, Anshumali Shrivastava. Arxiv 2025.

46. From Large to Super-Tiny: End-to-End Optimization for Cost-Efficient LLMs. Jiliang Ni, Jiachen Pu, Zhongyi Yang, Kun Zhou, Hui Wang, Xiaoliang Xiao, Dakui Wang, Xin Li, Jingfeng Luo, Conggang Hu. Arxiv 2025.

47. ImPart: Importance-Aware Delta-Sparsification for Improved Model Compression and Merging in LLMs. Yan Yang, Yixia Li, Hongru Wang, Xuetao Wei, Jianqiao Yu, Yun Chen, Guanhua Chen. Arxiv 2025.

48. On-Device Qwen2.5: Efficient LLM Inference with Model Compression and Hardware Acceleration. Maoyang Xiang, Ramesh Fernando, Bo Wang. Arxiv 2025.

49. Efficient LLMs with AMP: Attention Heads and MLP Pruning. Leandro Giusti Mugnaini, Bruno Lopes Yamamoto, Lucas Lauton de Alcantara, Victor Zacarias, Edson Bollis, Lucas Pellicer, Anna Helena Reali Costa, Artur Jordao. IJCNN 2025.

50. ParamΔ for Direct Weight Mixing: Post-Train Large Language Model at Zero Cost. Sheng Cao, Mingrui Wu, Karthik Prasad, Yuandong Tian, Zechun Liu. ICLR 2025.

51. ReplaceMe: Network Simplification via Layer Pruning and Linear Transformations. Dmitriy Shopkhoev, Ammar Ali, Magauiya Zhussip, Valentin Malykh, Stamatios Lefkimmiatis, Nikos Komodakis, Sergey Zagoruyko. Arxiv 2025.

52. Activation-Guided Consensus Merging for Large Language Models. Yuxuan Yao, Shuqi Liu, Zehua Liu, Qintong Li, Mingyang Liu, Xiongwei Han, Zhijiang Guo, Han Wu, Linqi Song. Arxiv 2025.

53. Breaking the Compression Ceiling: Data-Free Pipeline for Ultra-Efficient Delta Compression. Xiaohui Wang, Peng Ye, Chenyu Huang, Shenghe Zheng, Bo Zhang, Wanli Ouyang, Tao Chen. Arxiv 2025.

54. OrthoRank: Token Selection via Sink Token Orthogonality for Efficient LLM inference. Seungjun Shin, Jaehoon Oh, Dokwan Oh. ICML 2025.

55. LLM Compression: How Far Can We Go in Balancing Size and Performance?. Sahil Sk, Debasish Dhal, Sonal Khosla, Sk Shahid, Sambit Shekhar, Akash Dhaka, Shantipriya Parida, Dilip K. Prasad, Ondřej Bojar. Arxiv 2025.

56. One Shot vs. Iterative: Rethinking Pruning Strategies for Model Compression. Mikołaj Janusz, Tomasz Wojnar, Yawei Li, Luca Benini, Kamil Adamczewski. Arxiv 2025.

57. DTRNet: Dynamic Token Routing Network to Reduce Quadratic Costs in Transformers. Aman Sharma, Saeed Najafi, Parsa Farinneya, Benyamin Jamialahmadi, Marzieh S. Tahaei, Yuhe Fan, Mehdi Rezagholizadeh, Boxing Chen, Aref Jafari. Arxiv 2025.

58. The Thinking Spectrum: An Empirical Study of Tunable Reasoning in LLMs through Model Merging. Xiaochong Lan, Yu Zheng, Shiteng Cao, Yong Li. Arxiv 2025.

59. E3-Pruner: Towards Efficient, Economical, and Effective Layer Pruning for Large Language Models. Tao Yuan, Haoli Bai, Yinfei Pan, Xuyang Cao, Tianyu Zhang, Lu Hou, Ting Hu, Xianzhi Yu. Arxiv 2025.

9.3 Long CoT

1. Reasoning Path Compression: Compressing Generation Trajectories for Efficient LLM Reasoning. Jiwon Song, Dongwon Jo, Yulhwa Kim, Jae-Joon Kim. Arxiv 2025.

2. Can Pruning Improve Reasoning? Revisiting Long-CoT Compression with Capability in Mind for Better Reasoning. Shangziqi Zhao, Jiahao Yuan, Guisong Yang, Usman Naseem. Arxiv 2025.

3. FlashThink: An Early Exit Method For Efficient Reasoning. Guochao Jiang, Guofeng Quan, Zepeng Ding, Ziqin Luo, Dixuan Wang, Zheng Hu. Arxiv 2025.

4. Not All Tokens Are What You Need In Thinking. Hang Yuan, Bin Yu, Haotian Li, Shijun Yang, Christina Dan Wang, Zhou Yu, Xueyin Xu, Weizhen Qi, Kai Chen. Arxiv 2025.

5. TrimR: Verifier-based Training-Free Thinking Compression for Efficient Test-Time Scaling. Weizhe Lin, Xing Li, Zhiyuan Yang, Xiaojin Fu, Hui-Ling Zhen, Yaoyuan Wang, Xianzhi Yu, Wulong Liu, Xiaosong Li, Mingxuan Yuan. Arxiv 2025.

6. Efficient Long CoT Reasoning in Small Language Models. Zhaoyang Wang, Jinqi Jiang, Tian Qiu, Hui Liu, Xianfeng Tang, Huaxiu Yao. Arxiv 2025.

7. Efficient Reasoning via Chain of Unconscious Thought. Ruihan Gong, Yue Liu, Wenjie Qu, Mingzhe Du, Yufei He, Yingwei Ma, Yulin Chen, Xiang Liu, Yi Wen, Xinfeng Li, Ruidong Wang, Xinzhong Zhu, Bryan Hooi, Jiaheng Zhang. Arxiv 2025.

8. Hybrid Latent Reasoning via Reinforcement Learning. Zhenrui Yue, Bowen Jin, Huimin Zeng, Honglei Zhuang, Zhen Qin, Jinsung Yoon, Lanyu Shang, Jiawei Han, Dong Wang. Arxiv 2025.

9. System-1.5 Reasoning: Traversal in Language and Latent Spaces with Dynamic Shortcuts. Xiaoqiang Wang, Suyuchen Wang, Yun Zhu, Bang Liu. Arxiv 2025.

10. Optimizing Length Compression in Large Reasoning Models. Zhengxiang Cheng, Dongping Chen, Mingyang Fu, Tianyi Zhou. Arxiv 2025.

11. From Long to Short: LLMs Excel at Trimming Own Reasoning Chains. Wei Han, Geng Zhan, Sicheng Yu, Chenyu Wang, Bryan Hooi. Arxiv 2025.

12. Reasoning Efficiently Through Adaptive Chain-of-Thought Compression: A Self-Optimizing Framework. Kerui Huang, Shuhan Liu, Xing Hu, Tongtong Xu, Lingfeng Bao, Xin Xia. Arxiv 2025.

13. From Long to Lean: Performance-aware and Adaptive Chain-of-Thought Compression via Multi-round Refinement. Jianzhi Yan, Le Liu, Youcheng Pan, Shiwei Chen, Zike Yuan, Yang Xiang, Buzhou Tang. Arxiv 2025.

14. R-Capsule: Compressing High-Level Plans for Efficient Large Language Model Reasoning. Hongyu Shan, Mingyang Song, Chang Dai, Di Liang, Han Chen. Arxiv 2025.

15. Chain-of-Thought Compression Should Not Be Blind: V-Skip for Efficient Multimodal Reasoning via Dual-Path Anchoring. Dongxu Zhang, Yiding Sun, Cheng Tan, Wenbiao Yan, Ning Yang, Jihua Zhu, Hiajun Zhang. Arxiv 2026.

9.4 Latent

1. Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding. Haolin Chen, Yihao Feng, Zuxin Liu, Weiran Yao, Akshara Prabhakar, Shelby Heinecke, Ricky Ho, Phil Mui, Silvio Savarese, Caiming Xiong, Huan Wang. Arxiv 2024.        

2. Training Large Language Models to Reason in a Continuous Latent Space. Shibo Hao, Sainbayar Sukhbaatar, DiJia Su, Xian Li, Zhiting Hu, Jason Weston, Yuandong Tian. Arxiv 2024.        

3. Deliberation in Latent Space via Differentiable Cache Augmentation. Luyang Liu, Jonas Pfeiffer, Jiaxing Wu, Jun Xie, Arthur Szlam. Arxiv 2024.

4. Compressed Chain of Thought: Efficient Reasoning Through Dense Representations. Jeffrey Cheng, Benjamin Van Durme. Arxiv 2024.

5. Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach. Jonas Geiping, Sean McLeish, Neel Jain, John Kirchenbauer, Siddharth Singh, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Tom Goldstein. Arxiv 2025.        

6. Reasoning with Latent Thoughts: On the Power of Looped Transformers. Nikunj Saunshi, Nishanth Dikkala, Zhiyuan Li, Sanjiv Kumar, Sashank J. Reddi. Arxiv 2025.

7. Human Preferences in Large Language Model Latent Space: A Technical Analysis on the Reliability of Synthetic Data in Voting Outcome Prediction. Sarah Ball, Simeon Allmendinger, Frauke Kreuter, Niklas Kühl. Arxiv 2025.

8. CODI: Compressing Chain-of-Thought into Continuous Space via Self-Distillation. Zhenyi Shen, Hanqi Yan, Linhai Zhang, Zhanghao Hu, Yali Du, Yulan He. Arxiv 2025.

9. LLM Pretraining with Continuous Concepts. Jihoon Tack, Jack Lanchantin, Jane Yu, Andrew Cohen, Ilia Kulikov, Janice Lan, Shibo Hao, Yuandong Tian, Jason Weston, Xian Li. Arxiv 2025.        

10. Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning. Chi-Pin Huang, Yunze Man, Zhiding Yu, Min-Hung Chen, Jan Kautz, Yu-Chiang Frank Wang, Fu-En Yang. Arxiv 2026.        

10. Long Video and Image

10.1 Offline

1. EasyAnimate: A High-Performance Long Video Generation Method based on Transformer Architecture. Jiaqi Xu, Xinyi Zou, Kunzhe Huang, Yunkuo Chen, Bo Liu, MengLi Cheng, Xing Shi, Jun Huang. Arxiv 2024.

2. VideoTree: Adaptive Tree-based Video Representation for LLM Reasoning on Long Videos. Ziyang Wang, Shoubin Yu, Elias Stengel-Eskin, Jaehong Yoon, Feng Cheng, Gedas Bertasius, Mohit Bansal. Arxiv 2024.

3. PostDoc: Generating Poster from a Long Multimodal Document Using Deep Submodular Optimization. Vijay Jaisankar, Sambaran Bandyopadhyay, Kalp Vyas, Varre Chaitanya, Shwetha Somasundaram. Arxiv 2024.

4. Investigating Video Reasoning Capability of Large Language Models with Tropes in Movies. Hung-Ting Su, Chun-Tong Chao, Ya-Ching Hsu, Xudong Lin, Yulei Niu, Hung-Yi Lee, Winston H. Hsu. Arxiv 2024.        

5. Towards Event-oriented Long Video Understanding. Yifan Du, Kun Zhou, Yuqi Huo, Yifan Li, Wayne Xin Zhao, Haoyu Lu, Zijia Zhao, Bingning Wang, Weipeng Chen, Ji-Rong Wen. Arxiv 2024.

6. An End-to-End Speech Summarization Using Large Language Model. Hengchao Shang, Zongyao Li, Jiaxin Guo, Shaojun Li, Zhiqiang Rao, Yuanchang Luo, Daimeng Wei, Hao Yang. Arxiv 2024.

7. OmChat: A Recipe to Train Multimodal Language Models with Strong Long Context and Video Understanding. Tiancheng Zhao, Qianqian Zhang, Kyusong Lee, Peng Liu, Lu Zhang, Chunxin Fang, Jiajia Liao, Kelei Jiang, Yibo Ma, Ruochen Xu. Arxiv 2024.

8. MATE: Meet At The Embedding -- Connecting Images with Long Texts. Young Kyun Jang, Junmo Kang, Yong Jae Lee, Donghyun Kim. Arxiv 2024.

9. mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models. Jiabo Ye, Haiyang Xu, Haowei Liu, Anwen Hu, Ming Yan, Qi Qian, Ji Zhang, Fei Huang, Jingren Zhou. Arxiv 2024.

10. LongVILA: Scaling Long-Context Visual Language Models for Long Videos. Fuzhao Xue, Yukang Chen, Dacheng Li, Qinghao Hu, Ligeng Zhu, Xiuyu Li, Yunhao Fang, Haotian Tang, Shang Yang, Zhijian Liu, Ethan He, Hongxu Yin, Pavlo Molchanov, Jan Kautz, Linxi Fan, Yuke Zhu, Yao Lu, Song Han. Arxiv 2024.

11. DreamFactory: Pioneering Multi-Scene Long Video Generation with a Multi-Agent Framework. Zhifei Xie, Daniel Tang, Dingwei Tan, Jacques Klein, Tegawend F. Bissyand, Saad Ezzini. Arxiv 2024.

12. Bridging Episodes and Semantics: A Novel Framework for Long-Form Video Understanding. Gueter Josmy Faure, Jia-Fong Yeh, Min-Hung Chen, Hung-Ting Su, Winston H. Hsu, Shang-Hong Lai. ECCV 2024 Workshop.        

13. VideoLLaMB: Long-context Video Understanding with Recurrent Memory Bridges. Yuxuan Wang, Cihang Xie, Yang Liu, Zilong Zheng. Arxiv 2024.        

14. Longer is (Not Necessarily) Stronger: Punctuated Long-Sequence Training for Enhanced Speech Recognition and Translation. Nithin Rao Koluguri, Travis Bartley, Hainan Xu, Oleksii Hrinchuk, Jagadeesh Balam, Boris Ginsburg, Georg Kucsko. Arxiv 2024.

15. LongLLaVA: Scaling Multi-modal LLMs to 1000 Images Efficiently via Hybrid Architecture. Xidong Wang, Dingjie Song, Shunian Chen, Chen Zhang, Benyou Wang. Arxiv 2024.

16. VideoCLIP-XL: Advancing Long Description Understanding for Video CLIP Models. Jiapeng Wang, Chengyu Wang, Kunzhe Huang, Jun Huang, Lianwen Jin. Arxiv 2024.

17. Rethinking Visual Dependency in Long-Context Reasoning for Large Vision-Language Models. Yucheng Zhou, Zhi Rao, Jun Wan, Jianbing Shen. Arxiv 2024.

18. SlowFast-VGen: Slow-Fast Learning for Action-Driven Long Video Generation. Yining Hong, Beide Liu, Maxine Wu, Yuanhao Zhai, Kai-Wei Chang, Lingjie Li, Kevin Lin, Chung-Ching Lin, Jianfeng Wang, Zhengyuan Yang, Yingnian Wu, Lijuan Wang. Arxiv 2024.        

19. LLM2CLIP: Powerful Language Model Unlock Richer Visual Representation. Weiquan Huang, Aoqi Wu, Yifan Yang, Xufang Luo, Yuqing Yang, Liang Hu, Qi Dai, Xiyang Dai, Dongdong Chen, Chong Luo, Lili Qiu. NeurIPS 2024.

20. ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos. Tanveer Hannan, Md Mohaiminul Islam, Jindong Gu, Thomas Seidl, Gedas Bertasius. Arxiv 2024.

21. T2Vid: Translating Long Text into Multi-Image is the Catalyst for Video-LLMs. Shukang Yin, Chaoyou Fu, Sirui Zhao, Yunhang Shen, Chunjiang Ge, Yan Yang, Zuwei Long, Yuhan Dai, Tong Xu, Xing Sun, Ran He, Caifeng Shan, Enhong Chen. Arxiv 2024.

22. Owl-1: Omni World Model for Consistent Long Video Generation. Yuanhui Huang, Wenzhao Zheng, Yuan Gao, Xin Tao, Pengfei Wan, Di Zhang, Jie Zhou, Jiwen Lu. Arxiv 2024.

23. VCA: Video Curious Agent for Long Video Understanding. Zeyuan Yang, Delin Chen, Xueyang Yu, Maohao Shen, Chuang Gan. Arxiv 2024.

24. Enhancing Multi-Text Long Video Generation Consistency without Tuning: Time-Frequency Analysis, Prompt Alignment, and Theory. Xingyao Li, Fengzhuo Zhang, Jiachun Pan, Yunlong Hou, Vincent Y. F. Tan, Zhuoran Yang. Arxiv 2024.

25. ReTaKe: Reducing Temporal and Knowledge Redundancy for Long Video Understanding. Xiao Wang, Qingyi Si, Jianlong Wu, Shiyu Zhu, Li Cao, Liqiang Nie. Arxiv 2024.

26. LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token. Shaolei Zhang, Qingkai Fang, Zhe Yang, Yang Feng. Arxiv 2024.

27. Temporal Preference Optimization for Long-Form Video Understanding. Rui Li, Xiaohan Wang, Yuhui Zhang, Zeyu Wang, Serena Yeung-Levy. Arxiv 2025.        

28. Latent Swap Joint Diffusion for Long-Form Audio Generation. Yusheng Dai, Chenxi Wang, Chang Li, Chen Wang, Jun Du, Kewei Li, Ruoyu Wang, Jiefeng Ma, Lei Sun, Jianqing Gao. Arxiv 2025.

29. MALT Diffusion: Memory-Augmented Latent Transformers for Any-Length Video Generation. Sihyun Yu, Meera Hahn, Dan Kondratyuk, Jinwoo Shin, Agrim Gupta, José Lezama, Irfan Essa, David Ross, Jonathan Huang. Arxiv 2025.

30. VideoRoPE: What Makes for Good Video Rotary Position Embedding?. Xilin Wei, Xiaoran Liu, Yuhang Zang, Xiaoyi Dong, Pan Zhang, Yuhang Cao, Jian Tong, Haodong Duan, Qipeng Guo, Jiaqi Wang, Xipeng Qiu, Dahua Lin. Arxiv 2025.

31. Keyframe-oriented Vision Token Pruning: Enhancing Efficiency of Large Vision Language Models on Long-Form Video Processing. Yudong Liu, Jingwei Sun, Yueqian Lin, Jingyang Zhang, Ming Yin, Qinsi Wang, Jianyi Zhang, Hai Li, Yiran Chen. Arxiv 2025.

32. AdaReTaKe: Adaptive Redundancy Reduction to Perceive Longer for Video-language Understanding. Xiao Wang, Qingyi Si, Jianlong Wu, Shiyu Zhu, Li Cao, Liqiang Nie. Arxiv 2025.

33. Atlas: Multi-Scale Attention Improves Long Context Image Modeling. Kumar Krishna Agrawal, Long Lian, Longchao Liu, Natalia Harguindeguy, Boyi Li, Alexander Bick, Maggie Chung, Trevor Darrell, Adam Yala. Arxiv 2025.

34. Multimodal Long Video Modeling Based on Temporal Dynamic Context. Haoran Hao, Jiaming Han, Yiyuan Zhang, Xiangyu Yue. Arxiv 2025.

35. Deep Video Discovery: Agentic Search with Tool Use for Long-form Video Understanding. Xiaoyi Zhang, Zhaoyang Jia, Zongyu Guo, Jiahao Li, Bin Li, Houqiang Li, Yan Lu. Arxiv 2025.

36. DynTok: Dynamic Compression of Visual Tokens for Efficient and Effective Video Understanding. Hongzhi Zhang, Jingyuan Zhang, Xingguang Ji, Qi Wang, Fuzheng Zhang. Arxiv 2025.

37. EfficientVLA: Training-Free Acceleration and Compression for Vision-Language-Action Models. Yantai Yang, Yuhao Wang, Zichen Wen, Luo Zhongwei, Chang Zou, Zhipeng Zhang, Chuan Wen, Linfeng Zhang. Arxiv 2025.

38. InfiniPot-V: Memory-Constrained KV Cache Compression for Streaming Video Understanding. Minsoo Kim, Kyuhong Shim, Jungwook Choi, Simyung Chang. Arxiv 2025.

39. MadaKV: Adaptive Modality-Perception KV Cache Eviction for Efficient Multimodal Long-Context Inference. Kunxi Li, Zhonghua Jiang, Zhouzhou Shen, Zhaode Wang, Chengfei Lv, Shengyu Zhang, Fan Wu, Fei Wu. Arxiv 2025.

40. Machine Mental Imagery: Empower Multimodal Reasoning with Latent Visual Tokens. Zeyuan Yang, Xueyang Yu, Delin Chen, Maohao Shen, Chuang Gan. Arxiv 2025.

41. DyCoke: Dynamic Compression of Tokens for Fast Video Large Language Models. Keda Tao, Can Qin, Haoxuan You, Yang Sui, Huan Wang. ICCV 2025.

42. HiPrune: Training-Free Visual Token Pruning via Hierarchical Attention in Vision-Language Models. Jizhihui Liu, Feiyi Du, Guangdao Zhu, Niu Lian, Jun Li, Bin Chen. Arxiv 2025.

43. Representation Shift: Unifying Token Compression with FlashAttention. Joonmyung Choi, Sanghyeok Lee, Byungoh Ko, Eunseo Kim, Jihyung Kil, Hyunwoo J. Kim. ICCV 2025.

44. A Glimpse to Compress: Dynamic Visual Token Pruning for Large Vision-Language Models. Quan-Sheng Zeng, Yunheng Li, Qilong Wang, Peng-Tao Jiang, Zuxuan Wu, Ming-Ming Cheng, Qibin Hou. Arxiv 2025.

45. Free-MoRef: Instantly Multiplexing Context Perception Capabilities of Video-MLLMs within Single Inference. Kuo Wang, Quanlong Zheng, Junlin Xie, Yanhao Zhang, Jinguo Luo, Haonan Lu, Liang Lin, Fan Zhou, Guanbin Li. ICCV 2025.

46. E-VRAG: Enhancing Long Video Understanding with Resource-Efficient Retrieval Augmented Generation. Zeyu Xu, Junkang Zhang, Qiang Wang, Yi Liu. Arxiv 2025.

47. TSPO: Temporal Sampling Policy Optimization for Long-form Video Language Understanding. Canhui Tang, Zifan Han, Hongbo Sun, Sanping Zhou, Xuchong Zhang, Xin Wei, Ye Yuan, Huayu Zhang, Jinglin Xu, Hao Sun. Arxiv 2025.

48. Thinking With Videos: Multimodal Tool-Augmented Reinforcement Learning for Long Video Reasoning. Haoji Zhang, Xin Gu, Jiawen Li, Chixiang Ma, Sule Bai, Chubin Zhang, Bowen Zhang, Zhichao Zhou, Dongliang He, Yansong Tang. Arxiv 2025.

49. DynImg: Key Frames with Visual Prompts are Good Representation for Multi-Modal Video Understanding. Xiaoyi Bao, Chenwei Xie, Hao Tang, Tingyu Weng, Xiaofeng Wang, Yun Zheng, Xingang Wang. ICCV 2025.

50. Growing a Twig to Accelerate Large Vision-Language Models. Zhenwei Shao, Mingyang Wang, Zhou Yu, Wenwen Pan, Yan Yang, Tao Wei, Hongyuan Zhang, Ning Mao, Wei Chen, Jun Yu. ICCV 2025.

51. VFlowOpt: A Token Pruning Framework for LMMs with Visual Information Flow-Guided Optimization. Sihan Yang, Runsen Xu, Chenhang Cui, Tai Wang, Dahua Lin, Jiangmiao Pang. ICCV 2025.

52. AdaptInfer: Adaptive Token Pruning for Vision-Language Model Inference with Dynamical Text Guidance. Weichen Zhang, Zhui Zhu, Ningbo Li, Kebin Liu, Yunhao Liu. Arxiv 2025.

53. Fourier-VLM: Compressing Vision Tokens in the Frequency Domain for Large Vision-Language Models. Huanyu Wang, Jushi Kai, Haoli Bai, Lu Hou, Bo Jiang, Ziwei He, Zhouhan Lin. Arxiv 2025.

54. Episodic Memory Representation for Long-form Video Understanding. Yun Wang, Long Zhang, Jingren Liu, Jiaqi Yan, Zhanjie Zhang, Jiahao Zheng, Xun Yang, Dapeng Wu, Xiangyu Chen, Xuelong Li. Arxiv 2025.

55. MMTok: Multimodal Coverage Maximization for Efficient Inference of VLMs. Sixun Dong, Juhua Hu, Mian Zhang, Ming Yin, Yanjie Fu, Qi Qian. Arxiv 2025.

56. Video-MTR: Reinforced Multi-Turn Reasoning for Long Video Understanding. Yuan Xie, Tianshui Chen, Zheng Ge, Lionel Ni. Arxiv 2025.

57. MMG-Vid: Maximizing Marginal Gains at Segment-level and Token-level for Efficient Video LLMs. Junpeng Ma, Qizhe Zhang, Ming Lu, Zhibin Wang, Qiang Zhou, Jun Song, Shanghang Zhang. Arxiv 2025.

58. Video-LLMs with Temporal Visual Screening. Zheyu Fan, Jiateng Liu, Yuji Zhang, Zihan Wang, Yi R. (May) Fung, Manling Li, Heng Ji. Arxiv 2025.

59. Why 1 + 1 < 1 in Visual Token Pruning: Beyond Naive Integration via Multi-Objective Balanced Covering. Yangfu Li, Hongjian Zhan, Tianyi Chen, Qi Liu, Yue Lu. Arxiv 2025.

60. ADMIRE: ADaptive method to enhance Multiple Image REsolutions in text-rich multi-image understanding. Qipeng Zhu, Xiong Wang, Zhihong Lu, Jiangwei Lao, Congyun Jin, Jie Chen, Yingzhe Peng, Qi Zhu, Lianzhen Zhong, Jiajia Liu, Peng Wei, Jian Wang. KDD 2025.

61. Variation-aware Vision Token Dropping for Faster Large Vision-Language Models. Junjie Chen, Xuyang Liu, Zichen Wen, Yiyu Wang, Siteng Huang, Honggang Chen. Arxiv 2025.

62. Seeing More, Saying More: Lightweight Language Experts are Dynamic Video Token Compressors. Xiangchen Wang, Jinrui Zhang, Teng Wang, Haigang Zhang, Feng Zheng. EMNLP 2025.

63. LightVLM: Acceleraing Large Multimodal Models with Pyramid Token Merging and KV Cache Compression. Lianyu Hu, Fanhua Shang, Wei Feng, Liang Wan. EMNLP 2025.

64. Dense Video Understanding with Gated Residual Tokenization. Haichao Zhang, Wenhao Chai, Shwai He, Ang Li, Yun Fu. Arxiv 2025.

65. Eye Gaze Tells You Where to Compute: Gaze-Driven Efficient VLMs. Qinyu Chen, Jiawen Qi. Arxiv 2025.

66. LongLive: Real-time Interactive Long Video Generation. Shuai Yang, Wei Huang, Ruihang Chu, Yicheng Xiao, Yuyang Zhao, Xianbang Wang, Muyang Li, Enze Xie, Yingcong Chen, Yao Lu, Song Han, Yukang Chen. Arxiv 2025.

67. LongLive: Real-time Interactive Long Video Generation. Shuai Yang, Wei Huang, Ruihang Chu, Yicheng Xiao, Yuyang Zhao, Xianbang Wang, Muyang Li, Enze Xie, Yingcong Chen, Yao Lu, Song Han, Yukang Chen. Arxiv 2025.

68. Investigating Video Reasoning Capability of Large Language Models with Tropes in Movies. Hung-Ting Su, Chun-Tong Chao, Ya-Ching Hsu, Xudong Lin, Yulei Niu, Hung-Yi Lee, Winston H. Hsu. Arxiv 2024.

69. Training-Free Token Pruning via Zeroth-Order Gradient Estimation in Vision-Language Models. Youngeun Kim, Youjia Zhang, Huiling Liu, Aecheon Jung, Sunwoo Lee, Sungeun Hong. Arxiv 2025.

70. StreamForest: Efficient Online Video Understanding with Persistent Event Memory. Xiangyu Zeng, Kefan Qiu, Qingyu Zhang, Xinhao Li, Jing Wang, Jiaxin Li, Ziang Yan, Kun Tian, Meng Tian, Xinhai Zhao, Yi Wang, Limin Wang. NeurIPS 2025.

71. FameMind: Frame-Interleaved Video Reasoning via Reinforcement Learning. Haonan Ge, Yiwei Wang, Kai-Wei Chang, Hang Wu, Yujun Cai. Arxiv 2025.

72. SPIKE-RL: Video-LLMs meet Bayesian Surprise. Sahithya Ravi, Aditya Chinchure, Raymond T. Ng, Leonid Sigal, Vered Shwartz. Arxiv 2025.

73. VTPerception-R1: Enhancing Multimodal Reasoning via Explicit Visual and Textual Perceptual Grounding. Yizhuo Ding, Mingkang Chen, Zhibang Feng, Tong Xiao, Wanying Qu, Wenqi Shao, Yanwei Fu. Arxiv 2025.

74. LOVE-R1: Advancing Long Video Understanding with an Adaptive Zoom-in Mechanism via Multi-Step Reasoning. Shenghao Fu, Qize Yang, Yuan-Ming Li, Xihan Wei, Xiaohua Xie, Wei-Shi Zheng. Arxiv 2025.

75. Video Panels for Long Video Understanding. Lars Doorenbos, Federico Spurio, Juergen Gall. Arxiv 2025.

76. VideoNSA: Native Sparse Attention Scales Video Understanding. Enxin Song, Wenhao Chai, Shusheng Yang, Ethan Armand, Xiaojun Shan, Haiyang Xu, Jianwen Xie, Zhuowen Tu. Arxiv 2025.

77. Video-in-the-Loop: Span-Grounded Long Video QA with Interleaved Reasoning. Chendong Wang, Donglin Bai, Yifan Yang, Xiao Jin, Anlan Zhang, Rui Wang, Shiqi Jiang, Yuqing Yang, Hao Wu, Qi Dai, Chong Luo, Ting Cao, Lili Qiu, Suman Banerjee. Arxiv 2025.

78. Flow4Agent: Long-form Video Understanding via Motion Prior from Optical Flow. Ruyang Liu, Shangkun Sun, Haoran Tang, Ge Li, Wei Gao. ICCV 2025.

79. When Thinking Drifts: Evidential Grounding for Robust Video Reasoning. Mi Luo, Zihui Xue, Alex Dimakis, Kristen Grauman. Arxiv 2025.

80. MARC: Memory-Augmented RL Token Compression for Efficient Video Understanding. Peiran Wu, Zhuorui Yu, Yunze Liu, Chi-Hao Wu, Enmin Zhou, Junxiao Shen. Arxiv 2025.

81. D-CoDe: Scaling Image-Pretrained VLMs to Video via Dynamic Compression and Question Decomposition. Yiyang Huang, Yizhou Wang, Yun Fu. EMNLP 2025.

82. StreamingVLM: Real-Time Understanding for Infinite Video Streams. Ruyi Xu, Guangxuan Xiao, Yukang Chen, Liuning He, Kelly Peng, Yao Lu, Song Han. Arxiv 2025.

83. Vgent: Graph-based Retrieval-Reasoning-Augmented Generation For Long Video Understanding. Xiaoqian Shen, Wenxuan Zhang, Jun Chen, Mohamed Elhoseiny. NeurIPS 2025.

84. ZSPAPrune: Zero-Shot Prompt-Aware Token Pruning for Vision-Language Models. Pu Zhang, Yuwei Li, Xingyuan Xian, Guoming Tang. Arxiv 2025.

85. LongInsightBench: A Comprehensive Benchmark for Evaluating Omni-Modal Models on Human-Centric Long-Video Understanding. ZhaoYang Han, Qihan Lin, Hao Liang, Bowen Chen, Zhou Liu, Wentao Zhang. Arxiv 2025.

86. SparseVILA: Decoupling Visual Sparsity for Efficient VLM Inference. Samir Khaki, Junxian Guo, Jiaming Tang, Shang Yang, Yukang Chen, Konstantinos N. Plataniotis, Yao Lu, Song Han, Zhijian Liu. Arxiv 2025.

87. VisiPruner: Decoding Discontinuous Cross-Modal Dynamics for Efficient Multimodal LLMs. Yingqi Fan, Anhao Zhao, Jinlan Fu, Junlong Tong, Hui Su, Yijie Pan, Wei Zhang, Xiaoyu Shen. EMNLP 2025.

88. VisionSelector: End-to-End Learnable Visual Token Compression for Efficient Multimodal LLMs. Jiaying Zhu, Yurui Zhu, Xin Lu, Wenrui Yan, Dong Li, Kunlin Liu, Xueyang Fu, Zheng-Jun Zha. Arxiv 2025.

89. StreamingTOM: Streaming Token Compression for Efficient Video Understanding. Xueyi Chen, Keda Tao, Kele Shao, Huan Wang. Arxiv 2025.

90. Accelerating Vision Transformers with Adaptive Patch Sizes. Rohan Choudhury, JungEun Kim, Jinhyung Park, Eunho Yang, László A. Jeni, Kris M. Kitani. Arxiv 2025.

91. SeViCES: Unifying Semantic-Visual Evidence Consensus for Long Video Understanding. Yuan Sheng, Yanbin Hao, Chenxu Li, Shuo Wang, Xiangnan He. Arxiv 2025.

92. SCOPE: Saliency-Coverage Oriented Token Pruning for Efficient Multimodel LLMs. Jinhong Deng, Wen Li, Joey Tianyi Zhou, Yang He. NeurIPS 2025.

93. FLoC: Facility Location-Based Efficient Visual Token Compression for Long Video Understanding. Janghoon Cho, Jungsoo Lee, Munawar Hayat, Kyuwoong Hwang, Fatih Porikli, Sungha Choi. Arxiv 2025.

94. LiveStar: Live Streaming Assistant for Real-World Online Video Understanding. Zhenyu Yang, Kairui Zhang, Yuhang Hu, Bing Wang, Shengsheng Qian, Bin Wen, Fan Yang, Tingting Gao, Weiming Dong, Changsheng Xu. NeurIPS 2025.

95. TimeSearch-R: Adaptive Temporal Search for Long-Form Video Understanding via Self-Verification Reinforcement Learning. Junwen Pan, Qizhe Zhang, Rui Zhang, Ming Lu, Xin Wan, Yuan Zhang, Chang Liu, Qi She. Arxiv 2025.

96. Can Visual Input Be Compressed? A Visual Token Compression Benchmark for Large Multimodal Models. Tianfan Peng, Yuntao Du, Pengzhou Ji, Shijie Dong, Kailin Jiang, Mingchuan Ma, Yijun Tian, Jinhe Bi, Qian Li, Wei Du, Feng Xiao, Lizhen Cui. Arxiv 2025.

97. TimeViper: A Hybrid Mamba-Transformer Vision-Language Model for Efficient Long Video Understanding. Boshen Xu, Zihan Xiao, Jiaze Li, Jianzhong Ju, Zhenbo Luo, Jian Luan, Qin Jin. Arxiv 2025.

98. VideoCompressa: Data-Efficient Video Understanding via Joint Temporal Compression and Spatial Reconstruction. Shaobo Wang, Tianle Niu, Runkang Yang, Deshan Liu, Xu He, Zichen Wen, Conghui He, Xuming Hu, Linfeng Zhang. Arxiv 2025.

99. Test-Time Temporal Sampling for Efficient MLLM Video Understanding. Kaibin Wang, Mingbao Lin. Arxiv 2025.

100. FastMMoE: Accelerating Multimodal Large Language Models through Dynamic Expert Activation and Routing-Aware Token Pruning. Guoyang Xia, Yifeng Ding, Fengfa Li, Lei Ren, Wei Chen, Fangxiang Feng, Xiaojie Wang. Arxiv 2025.

101. LLaVA-UHD v3: Progressive Visual Compression for Efficient Native-Resolution Encoding in MLLMs. Shichu Sun, Yichen Zhang, Haolin Song, Zonghao Guo, Chi Chen, Yidan Zhang, Yuan Yao, Zhiyuan Liu, Maosong Sun. Arxiv 2025.

102. LongVT: Incentivizing "Thinking with Long Videos" via Native Tool Calling. Zuhao Yang, Sudong Wang, Kaichen Zhang, Keming Wu, Sicong Leng, Yifan Zhang, Chengwei Qin, Shijian Lu, Xingxuan Li, Lidong Bing. Arxiv 2025.

103. WorldMM: Dynamic Multimodal Memory Agent for Long Video Reasoning. Woongyeong Yeo, Kangsan Kim, Jaehong Yoon, Sung Ju Hwang. Arxiv 2025.

104. VLM-Pruner: Buffering for Spatial Sparsity in an Efficient VLM Centrifugal Token Pruning Paradigm. Zhenkai Wu, Xiaowen Ma, Zhenliang Ni, Dengming Zhang, Han Shu, Xin Jiang, Xinghao Chen. Arxiv 2025.

105. AdaptVision: Efficient Vision-Language Models via Adaptive Visual Acquisition. Zichuan Lin, Yicheng Liu, Yang Yang, Lvfang Tao, Deheng Ye. Arxiv 2025.

106. Zoom-Zero: Reinforced Coarse-to-Fine Video Understanding via Temporal Zoom-in. Xiaoqian Shen, Min-Hung Chen, Yu-Chiang Frank Wang, Mohamed Elhoseiny, Ryo Hachiuma. Arxiv 2025.

107. Compressor-VLA: Instruction-Guided Visual Token Compression for Efficient Robotic Manipulation. Juntao Gao, Feiyang Ye, Jing Zhang, Wenjing Qian. Arxiv 2025.

108. UniComp: Rethinking Video Compression Through Informational Uniqueness. Chao Yuan, Shimin Chen, Minliang Lin, Limeng Qiao, Guanglu Wan, Lin Ma. Arxiv 2025.

109. EEA: Exploration-Exploitation Agent for Long Video Understanding. Te Yang, Xiangyu Zhu, Bo Wang, Quan Chen, Peng Jiang, Zhen Lei. Arxiv 2025.

110. TimeLens: Rethinking Video Temporal Grounding with Multimodal LLMs. Jun Zhang, Teng Wang, Yuying Ge, Yixiao Ge, Xinhao Li, Ying Shan, Limin Wang. Arxiv 2025.

111. SAGE: Training Smart Any-Horizon Agents for Long Video Reasoning with Reinforcement Learning. Jitesh Jain, Jialuo Li, Zixian Ma, Jieyu Zhang, Chris Dongjoo Kim, Sangho Lee, Rohun Tripathi, Tanmay Gupta, Christopher Clark, Humphrey Shi. Arxiv 2025.

112. MMViR: A Multi-Modal and Multi-Granularity Representation for Long-range Video Understanding. Zizhong Li, Haopeng Zhang, Jiawei Zhang. Arxiv 2026.

113. See More, Store Less: Memory-Efficient Resolution for Video Moment Retrieval. Mingyu Jeon, Sungjin Han, Jinkwon Hwang, Minchol Kwon, Jonghee Kim, Junyeong Kim. Arxiv 2026.

114. VideoAuto-R1: Video Auto Reasoning via Thinking Once, Answering Twice. Shuming Liu, Mingchen Zhuge, Changsheng Zhao, Jun Chen, Lemeng Wu, Zechun Liu, Chenchen Zhu, Zhipeng Cai, Chong Zhou, Haozhe Liu, Ernie Chang, Saksham Suri, Hongyu Xu, Qi Qian, Wei Wen, Balakrishnan Varadarajan, Zhuang Liu, Hu Xu, Florian Bordes, Raghuraman Krishnamoorthi, Bernard Ghanem, Vikas Chandra, Yunyang Xiong. Arxiv 2026.

115. Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding. Christopher Clark, Jieyu Zhang, Zixian Ma, Jae Sung Park, Mohammadreza Salehi, Rohun Tripathi, Sangho Lee, Zhongzheng Ren, Chris Dongjoo Kim, Yinuo Yang, Vincent Shao, Yue Yang, Weikai Huang, Ziqi Gao, Taira Anderson, Jianrui Zhang, Jitesh Jain, George Stoica, Winson Han, Ali Farhadi, Ranjay Krishna. Arxiv 2026.

116. Hierarchical Long Video Understanding with Audiovisual Entity Cohesion and Agentic Search. Xinlei Yin, Xiulian Peng, Xiao Li, Zhiwei Xiong, Yan Lu. Arxiv 2026.

117. Beyond Accuracy: Evaluating Grounded Visual Evidence in Thinking with Images (ViEBench). Xuchen Li, Xuzhao Li, Renjie Pi, Shiyu Hu, Jian Zhao, Jiahui Gao. Arxiv 2026.

118. HIPPO: Accelerating Video Large Language Models Inference via Holistic-aware Parallel Speculative Decoding. Qitan Lv, Tianyu Liu, Wen Wu, Xuenan Xu, Bowen Zhou, Feng Wu, Chao Zhang. Arxiv 2026.

119. Soft Tail-dropping for Adaptive Visual Tokenization. Zeyuan Chen, Kai Zhang, Zhuowen Tu, Yuanjun Xiong. Arxiv 2026.

120. HERMES: KV Cache as Hierarchical Memory for Efficient Streaming Video Understanding. Haowei Zhang, Shudong Yang, Jinlan Fu, See-Kiong Ng, Xipeng Qiu. Arxiv 2026.

121. LongVideo-R1: Smart Navigation for Low-cost Long Video Understanding. Jihao Qiu, Lingxi Xie, Xinyue Huo, Qi Tian, Qixiang Ye. Arxiv 2026.

122. OneVision-Encoder: Codec-Aligned Sparsity as a Foundational Principle for Multimodal Intelligence. Feilong Tang, Xiang An, Yunyao Yan, Yin Xie, Bin Qin, Kaicheng Yang, Yifei Shen, Yuanhan Zhang, Chunyuan Li, Shikun Feng, Changrui Chen, Huajie Tan, Ming Hu, Manyuan Zhang, Bo Li, Ziyong Feng, Ziwei Liu, Zongyuan Ge, Jiankang Deng. Arxiv 2026.

10.2 Streaming

1. Speak While Watching: Unleashing TRUE Real-Time Video Understanding Capability of Multimodal Large Language Models. Junyan Lin, Junlong Tong, Hao Wu, Jialiang Zhang, Jinming Liu, Xin Jin, Xiaoyu Shen. Arxiv 2026.

2. HERMES: KV Cache as Hierarchical Memory for Efficient Streaming Video Understanding. Haowei Zhang, Shudong Yang, Jinlan Fu, See-Kiong Ng, Xipeng Qiu. Arxiv 2026.

3. XStreamVGGT: Extremely Memory-Efficient Streaming Vision Geometry Grounded Transformer with KV Cache Compression. Zunhai Su, Weihao Ye, Hansen Feng, Keyu Fan, Jing Zhang, Dahai Yu, Zhengwu Liu, Ngai Wong. Arxiv 2026.

10.3 Frame Selection

1. Think-Clip-Sample: Slow-Fast Frame Selection for Video Understanding. Wenhui Tan, Ruihua Song, Jiaze Li, Jianzhong Ju, Zhenbo Luo. ICASSP 2026.

2. KeyVideoLLM: Towards Large-scale Video Keyframe Selection. Hao Liang, Jiapeng Li, Tianyi Bai, Chong Chen, Conghui He, Bin Cui, Wentao Zhang. Arxiv 2024.

3. Adaptive Keyframe Sampling for Long Video Understanding. Xi Tang, Jihao Qiu, Lingxi Xie, Yunjie Tian, Jianbin Jiao, Qixiang Ye. CVPR 2025.

4. Logic-in-Frames: Dynamic Keyframe Search via Visual Semantic-Logical Verification for Long Video Understanding. Weiyu Guo, Ziyang Chen, Shaoguang Wang, Jianxiang He, Yijie Xu, Jinhui Ye, Ying Sun, Hui Xiong. Arxiv 2025.

5. Q-Frame: Query-aware Frame Selection and Multi-Resolution Adaptation for Video-LLMs. Shaojie Zhang, Jiahui Yang, Jianqin Yin, Zhenbo Luo, Jian Luan. ICCV 2025.

6. FrameThinker: Learning to Think with Long Videos via Multi-Turn Frame Spotlighting. Zefeng He, Xiaoye Qu, Yafu Li, Siyuan Huang, Daizong Liu, Yu Cheng. Arxiv 2025.

7. From Frames to Clips: Efficient Key Clip Selection for Long-Form Video Understanding. Guangyu Sun, Archit Singhal, Burak Uzkent, Mubarak Shah, Chen Chen, Garin Kessler. Arxiv 2025.

8. A.I.R.: Enabling Adaptive, Iterative, and Reasoning-based Frame Selection For Video Question Answering. Yuanhao Zou, Shengji Jin, Andong Deng, Youpeng Zhao, Jun Wang, Chen Chen. Arxiv 2025.

9. FOCUS: Efficient Keyframe Selection for Long Video Understanding. Zirui Zhu, Hailun Xu, Yang Luo, Yong Liu, Kanchan Sarkar, Zhenheng Yang, Yang You. Arxiv 2025.

10. Divide, then Ground: Adapting Frame Selection to Query Types for Long-Form Video Understanding. Jialuo Li, Bin Li, Jiahao Li, Yan Lu. Arxiv 2025.

10.4 Vision Language Action

1. Fast-ThinkAct: Efficient Vision-Language-Action Reasoning via Verbalizable Latent Planning. Chi-Pin Huang, Yunze Man, Zhiding Yu, Min-Hung Chen, Jan Kautz, Yu-Chiang Frank Wang, Fu-En Yang. Arxiv 2026.

2. BFA++: Hierarchical Best-Feature-Aware Token Prune for Multi-View Vision Language Action Model. Haosheng Li, Weixin Mao, Zihan Lan, Hongwei Xiong, Hongan Wang, Chenyang Si, Ziwei Liu, Xiaoming Deng, Hua Chen. Arxiv 2026.

11. Benchmark and Evaluation

11.1 LLM

1. Long Range Arena : A Benchmark for Efficient Transformers. Yi Tay, Mostafa Dehghani, Samira Abnar, Yikang Shen, Dara Bahri, Philip Pham, Jinfeng Rao, Liu Yang, Sebastian Ruder, Donald Metzler. ICLR 2021.

2. LOT: A Story-Centric Benchmark for Evaluating Chinese Long Text Understanding and Generation. Jian Guan, Zhuoer Feng, Yamei Chen, Ruilin He, Xiaoxi Mao, Changjie Fan, Minlie Huang. TACL 2022.

3. SCROLLS: Standardized CompaRison Over Long Language Sequences. Uri Shaham, Elad Segal, Maor Ivgi, Avia Efrat, Ori Yoran, Adi Haviv, Ankit Gupta, Wenhan Xiong, Mor Geva, Jonathan Berant, Omer Levy. EMNLP 2022.

4. MuLD: The Multitask Long Document Benchmark. George Hudson, Noura Al Moubayed. LREC 2022.

5. Lost in the Middle: How Language Models Use Long Contexts. Nelson F. Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, Percy Liang. Arxiv 2023.

6. L-Eval: Instituting Standardized Evaluation for Long Context Language Models. Chenxin An, Shansan Gong, Ming Zhong, Mukai Li, Jun Zhang, Lingpeng Kong, Xipeng Qiu. Arxiv 2023.

7. LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding. Yushi Bai, Xin Lv, Jiajie Zhang, Hongchang Lyu, Jiankai Tang, Zhidian Huang, Zhengxiao Du, Xiao Liu, Aohan Zeng, Lei Hou, Yuxiao Dong, Jie Tang, Juanzi Li. Arxiv 2023.

8. Content Reduction, Surprisal and Information Density Estimation for Long Documents. Shaoxiong Ji, Wei Sun, Pekka Marttinen. Arxiv 2023.

9. BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models. Zican Dong, Tianyi Tang, Junyi Li, Wayne Xin Zhao, Ji-Rong Wen. Arxiv 2023.

10. Retrieval meets Long Context Large Language Models. Peng Xu, Wei Ping, Xianchao Wu, Lawrence McAfee, Chen Zhu, Zihan Liu, Sandeep Subramanian, Evelina Bakhturina, Mohammad Shoeybi, Bryan Catanzaro. Arxiv 2023.

11. LooGLE: Long Context Evaluation for Long-Context Language Models. Jiaqi Li, Mengmeng Wang, Zilong Zheng, Muhan Zhang. Arxiv 2023.

12. The Impact of Reasoning Step Length on Large Language Models. Mingyu Jin, Qinkai Yu, Dong shu, Haiyan Zhao, Wenyue Hua, Yanda Meng, Yongfeng Zhang, Mengnan Du. Arxiv 2024.

13. DocFinQA: A Long-Context Financial Reasoning Dataset. Varshini Reddy, Rik Koncel-Kedziorski, Viet Dac Lai, Chris Tanner. Arxiv 2024.

14. LongFin: A Multimodal Document Understanding Model for Long Financial Domain Documents. Ahmed Masry, Amir Hajian. Arxiv 2024.

15. PROXYQA: An Alternative Framework for Evaluating Long-Form Text Generation with Large Language Models. Haochen Tan, Zhijiang Guo, Zhan Shi, Lu Xu, Zhili Liu, Xiaoguang Li, Yasheng Wang, Lifeng Shang, Qun Liu, Linqi Song. Arxiv 2024.

16. LongHealth: A Question Answering Benchmark with Long Clinical Documents. Lisa Adams, Felix Busch, Tianyu Han, Jean-Baptiste Excoffier, Matthieu Ortala, Alexander Löser, Hugo JWL. Aerts, Jakob Nikolas Kather, Daniel Truhn, Keno Bressem. Arxiv 2024.

17. Long-form evaluation of model editing. Domenic Rosati, Robie Gonzales, Jinkun Chen, Xuemin Yu, Melis Erkan, Yahya Kayani, Satya Deepika Chavatapalli, Frank Rudzicz, Hassan Sajjad. Arxiv 2024.

18. In Search of Needles in a 10M Haystack: Recurrent Memory Finds What LLMs Miss. Yuri Kuratov, Aydar Bulatov, Petr Anokhin, Dmitry Sorokin, Artyom Sorokin, Mikhail Burtsev. Arxiv 2024.

19. ∞Bench: Extending Long Context Evaluation Beyond 100K Tokens. Xinrong Zhang, Yingfa Chen, Shengding Hu, Zihang Xu, Junhao Chen, Moo Khai Hao, Xu Han, Zhen Leng Thai, Shuo Wang, Zhiyuan Liu, Maosong Sun. Arxiv 2024.

20. Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models. Mosh Levy, Alon Jacoby, Yoav Goldberg. Arxiv 2024.

21. Evaluating Very Long-Term Conversational Memory of LLM Agents. Adyasha Maharana, Dong-Ho Lee, Sergey Tulyakov, Mohit Bansal, Francesco Barbieri, Yuwei Fang. Arxiv 2024.

22. Language Models as Science Tutors. Alexis Chevalier, Jiayi Geng, Alexander Wettig, Howard Chen, Sebastian Mizera, Toni Annala, Max Jameson Aragon, Arturo Rodríguez Fanlo, Simon Frieder, Simon Machado, Akshara Prabhakar, Ellie Thieu, Jiachen T. Wang, Zirui Wang, Xindi Wu, Mengzhou Xia, Wenhan Jia, Jiatong Yu, Jun-Jie Zhu, Zhiyong Jason Ren, Sanjeev Arora, Danqi Chen. Arxiv 2024.

23. Needle in a haystack - pressure testing llms. Kamradt, G. Github 2024.

24. In Search of Needles in a 11M Haystack: Recurrent Memory Finds What LLMs Miss. Yuri Kuratov, Aydar Bulatov, Petr Anokhin, Dmitry Sorokin, Artyom Sorokin, Mikhail Burtsev. Arxiv 2024.

25. LV-Eval: A Balanced Long-Context Benchmark with 5 Length Levels Up to 256K. Tao Yuan, Xuefei Ning, Dong Zhou, Zhijie Yang, Shiyao Li, Minghui Zhuang, Zheyue Tan, Zhuyu Yao, Dahua Lin, Boxun Li, Guohao Dai, Shengen Yan, Yu Wang. Arxiv 2024.

26. Counting-Stars: A Simple, Efficient, and Reasonable Strategy for Evaluating Long-Context Large Language Models. Mingyang Song, Mao Zheng, Xuan Luo. Arxiv 2024.

27. NovelQA: A Benchmark for Long-Range Novel Question Answering. Cunxiang Wang, Ruoxi Ning, Boqi Pan, Tonghui Wu, Qipeng Guo, Cheng Deng, Guangsheng Bao, Qian Wang, Yue Zhang. Arxiv 2024.

28. Long-form factuality in large language models. Jerry Wei, Chengrun Yang, Xinying Song, Yifeng Lu, Nathan Hu, Dustin Tran, Daiyi Peng, Ruibo Liu, Da Huang, Cosmo Du, Quoc V. Le. Arxiv 2024.

29. LUQ: Long-text Uncertainty Quantification for LLMs. JCaiqi Zhang, Fangyu Liu, Marco Basaldella, Nigel Collier. Arxiv 2024.

30. CLongEval: A Chinese Benchmark for Evaluating Long-Context Large Language Models. Zexuan Qiu, Jingjing Li, Shijue Huang, Wanjun Zhong, Irwin King. Arxiv 2024.

31. Long-context LLMs Struggle with Long In-context Learning. Tianle Li, Ge Zhang, Quy Duc Do, Xiang Yue, Wenhu Chen. Arxiv 2024.

32. CLAPNQ: Cohesive Long-form Answers from Passages in Natural Questions for RAG systems. Sara Rosenthal, Avirup Sil, Radu Florian, Salim Roukos. Arxiv 2024.

33. XL2Bench: A Benchmark for Extremely Long Context Understanding with Long-range Dependencies. Xuanfan Ni, Hengyi Cai, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Piji Li. Arxiv 2024.

34. Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors. Ido Amos, Jonathan Berant, Ankit Gupta. ICLR 2024 Oral.

35. Ada-LEval: Evaluating long-context LLMs with length-adaptable benchmarks. Chonghua Wang, Haodong Duan, Songyang Zhang, Dahua Lin, Kai Chen. Arxiv 2024.

36. RULER: What's the Real Context Size of Your Long-Context Language Models?. Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, Shantanu Acharya, Dima Rekesh, Fei Jia, Boris Ginsburg. Arxiv 2024.

37. LongEmbed: Extending Embedding Models for Long Context Retrieval. Dawei Zhu, Liang Wang, Nan Yang, Yifan Song, Wenhao Wu, Furu Wei, Sujian Li. Arxiv 2024.

38. Make Your LLM Fully Utilize the Context. Shengnan An, Zexiong Ma, Zeqi Lin, Nanning Zheng, Jian-Guang Lou. Arxiv 2024.

39. S3Eval: A Synthetic, Scalable, Systematic Evaluation Suite for Large Language Models. Fangyu Lei, Qian Liu, Yiming Huang, Shizhu He, Jun Zhao, Kang Liu. NAACL 2024.

40. In-Context Learning with Long-Context Models: An In-Depth Exploration. Amanda Bertsch, Maor Ivgi, Uri Alon, Jonathan Berant, Matthew R. Gormley, Graham Neubig. Arxiv 2024.

41. Many-shot Jailbreaking. Anthropic 2024.

42. DOLOMITES: Domain-Specific Long-Form Methodical Tasks. Chaitanya Malaviya, Priyanka Agrawal, Kuzman Ganchev, Pranesh Srinivasan, Fantine Huot, Jonathan Berant, Mark Yatskar, Dipanjan Das, Mirella Lapata, Chris Alberti. Arxiv 2024.

43. Challenges in Deploying Long-Context Transformers: A Theoretical Peak Performance Analysis. Yao Fu. Arxiv 2024.

44. FinTextQA: A Dataset for Long-form Financial Question Answering. Jian Chen, Peilin Zhou, Yining Hua, Yingxin Loh, Kehui Chen, Ziyuan Li, Bing Zhu, Junwei Liang. Arxiv 2024.

45. A Multi-Perspective Analysis of Memorization in Large Language Models. Bowen Chen, Namgi Han, Yusuke Miyao. Arxiv 2024.

46. OLAPH: Improving Factuality in Biomedical Long-form Question Answering. Minbyul Jeong, Hyeon Hwang, Chanwoong Yoon, Taewhoo Lee, Jaewoo Kang. Arxiv 2024.

47. Can LLMs Solve longer Math Word Problems Better?. Xin Xu, Tong Xiao, Zitong Chao, Zhenya Huang, Can Yang, Yang Wang. Arxiv 2024.

48. Base of RoPE Bounds Context Length. Xin Men, Mingyu Xu, Bingning Wang, Qingyu Zhang, Hongyu Lin, Xianpei Han, Weipeng Chen. Arxiv 2024.

49. Many-shot In-Context Learning. Rishabh Agarwal, Avi Singh, Lei M. Zhang, Bernd Bohnet, Luis Rosias, Stephanie Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal Behbahani, Aleksandra Faust, Hugo Larochelle. Arxiv 2024.

50. Long Context is Not Long at All: A Prospector of Long-Dependency Data for Large Language Models. Longze Chen, Ziqiang Liu, Wanwei He, Yunshui Li, Run Luo, Min Yang. Arxiv 2024.

51. Language Models Need Inductive Biases to Count Inductively. Yingshan Chang, Yonatan Bisk. Arxiv 2024.

52. Analyzing Temporal Complex Events with Large Language Models? A Benchmark towards Temporal, Long Context Understanding. Zhihan Zhang, Yixin Cao, Chenchen Ye, Yunshan Ma, Lizi Liao, Tat-Seng Chua. Arxiv 2024.

53. CRAG -- Comprehensive RAG Benchmark. Xiao Yang, Kai Sun, Hao Xin, Yushi Sun, Nikita Bhalla, Xiangsen Chen, Sajal Choudhary, Rongze Daniel Gui, Ziran Will Jiang, Ziyu Jiang, Lingkun Kong, Brian Moran, Jiaqi Wang, Yifan Ethan Xu, An Yan, Chenyu Yang, Eting Yuan, Hanwen Zha, Nan Tang, Lei Chen, Nicolas Scheffer, Yue Liu, Nirav Shah, Rakesh Wanga, Anuj Kumar, Wen-tau Yih, Xin Luna Dong. Arxiv 2024.

54. An Empirical Study of Mamba-based Language Models. Roger Waleffe, Wonmin Byeon, Duncan Riach, Brandon Norick, Vijay Korthikanti, Tri Dao, Albert Gu, Ali Hatamizadeh, Sudhakar Singh, Deepak Narayanan, Garvit Kulshreshtha, Vartika Singh, Jared Casper, Jan Kautz, Mohammad Shoeybi, Bryan Catanzaro. Arxiv 2024.

55. BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack. Yuri Kuratov, Aydar Bulatov, Petr Anokhin, Ivan Rodkin, Dmitry Sorokin, Artyom Sorokin, Mikhail Burtsev. Arxiv 2024.

56. Can Many-Shot In-Context Learning Help Long-Context LLM Judges? See More, Judge Better!. Mingyang Song, Mao Zheng, Xuan Luo. Arxiv 2024.

57. What Kinds of Tokens Benefit from Distant Text? An Analysis on Long Context Language Modeling. Yutong Hu, Quzhe Huang, Kangcheng Luo, Yansong Feng. Arxiv 2024.

58. Understanding the RoPE Extensions of Long-Context LLMs: An Attention Perspective. Meizhi Zhong, Chen Zhang, Yikun Lei, Xikai Liu, Yan Gao, Yao Hu, Kehai Chen, Min Zhang. Arxiv 2024.

59. Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More?. Jinhyuk Lee, Anthony Chen, Zhuyun Dai, Dheeru Dua, Devendra Singh Sachan, Michael Boratko, Yi Luan, Sébastien M. R. Arnold, Vincent Perot, Siddharth Dalmia, Hexiang Hu, Xudong Lin, Panupong Pasupat, Aida Amini, Jeremy R. Cole, Sebastian Riedel, Iftekhar Naim, Ming-Wei Chang, Kelvin Guu. Arxiv 2024.

60. Insights into LLM Long-Context Failures: When Transformers Know but Don't Tell. Taiming Lu, Muhan Gao, Kuai Yu, Adam Byerly, Daniel Khashabi. Arxiv 2024.

61. MedOdyssey: A Medical Domain Benchmark for Long Context Evaluation Up to 200K Tokens. Yongqi Fan, Hongli Sun, Kui Xue, Xiaofan Zhang, Shaoting Zhang, Tong Ruan. Arxiv 2024.

62. USDC: A Dataset of $\underline{U}$ser $\underline{S}$tance and $\underline{D}$ogmatism in Long $\underline{C}$onversations. Mounika Marreddy, Subba Reddy Oota, Venkata Charan Chinni, Manish Gupta, Lucie Flek. Arxiv 2024.

63. Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization. Cheng-Yu Hsieh, Yung-Sung Chuang, Chun-Liang Li, Zifeng Wang, Long T. Le, Abhishek Kumar, James Glass, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister. Arxiv 2024.

64. One Thousand and One Pairs: A "novel" challenge for long-context language models. Marzena Karpinska, Katherine Thai, Kyle Lo, Tanya Goyal, Mohit Iyyer. Arxiv 2024.        

65. LongIns: A Challenging Long-context Instruction-based Exam for LLMs. Shawn Gavin, Tuney Zheng, Jiaheng Liu, Quehry Que, Noah Wang, Jian Yang, Chenchen Zhang, Wenhao Huang, Wenhu Chen, Ge Zhang. Arxiv 2024.

66. Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA. Minzheng Wang, Longze Chen, Cheng Fu, Shengyi Liao, Xinghua Zhang, Bingli Wu, Haiyang Yu, Nan Xu, Lei Zhang, Run Luo, Yunshui Li, Min Yang, Fei Huang, Yongbin Li. Arxiv 2024.

67. VERISCORE: Evaluating the factuality of verifiable claims in long-form text generation. Yixiao Song, Yekyung Kim, Mohit Iyyer. Arxiv 2024.

68. ToolBeHonest: A Multi-level Hallucination Diagnostic Benchmark for Tool-Augmented Large Language Models. Yuxiang Zhang, Jing Chen, Junjie Wang, Yaxin Liu, Cheng Yang, Chufan Shi, Xinyu Zhu, Zihao Lin, Hanwen Wan, Yujiu Yang, Tetsuya Sakai, Tian Feng, Hayato Yamana. Arxiv 2024.

69. KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark of Long Context Capable Approaches. Jiayi Yuan, Hongyi Liu, Shaochen (Henry)Zhong, Yu-Neng Chuang, Songchen Li, Guanchu Wang, Duy Le, Hongye Jin, Vipin Chaudhary, Zhaozhuo Xu, Zirui Liu, Xia Hu. Arxiv 2024.

70. Is It Really Long Context if All You Need Is Retrieval? Towards Genuinely Difficult Long Context NLP. Omer Goldman, Alon Jacovi, Aviv Slobodkin, Aviya Maimon, Ido Dagan, Reut Tsarfaty. Arxiv 2024.

71. Summary of a Haystack: A Challenge to Long-Context LLMs and RAG Systems. Philippe Laban, Alexander R. Fabbri, Caiming Xiong, Chien-Sheng Wu. Arxiv 2024.

72. Entity-Level Sentiment: More than the Sum of Its Parts. Egil Rønningstad, Roman Klinger, Erik Velldal, Lilja Øvrelid. Arxiv 2024.

73. Evaluating Language Model Context Windows: A "Working Memory" Test and Inference-time Correction. Amanda Dsouza, Christopher Glaze, Changho Shin, Frederic Sala. Arxiv 2024.

74. RAG vs. Long Context: Examining Frontier Large Language Models for Environmental Review Document Comprehension. Hung Phan, Anurag Acharya, Sarthak Chaturvedi, Shivam Sharma, Mike Parker, Dan Nally, Ali Jannesari, Karl Pazdernik, Mahantesh Halappanavar, Sai Munikoti, Sameera Horawalavithana. Arxiv 2024.

75. Attribute or Abstain: Large Language Models as Long Document Assistants. Jan Buchmann, Xiao Liu, Iryna Gurevych. Arxiv 2024.

76. How Well Can a Long Sequence Model Model Long Sequences? Comparing Architechtural Inductive Biases on Long-Context Abilities. Jerry Huang. Arxiv 2024.

77. DOCBENCH: A Benchmark for Evaluating LLM-based Document Reading Systems. Anni Zou, Wenhao Yu, Hongming Zhang, Kaixin Ma, Deng Cai, Zhuosheng Zhang, Hai Zhao, Dong Yu. Arxiv 2024.

78. NeedleBench: Can LLMs Do Retrieval and Reasoning in 1 Million Context Window?. Mo Li, Songyang Zhang, Yunxin Liu, Kai Chen. Arxiv 2024.

79. LongLaMP: A Benchmark for Personalized Long-form Text Generation. Ishita Kumar, Snigdha Viswanathan, Sushrita Yerra, Alireza Salemi, Ryan A. Rossi, Franck Dernoncourt, Hanieh Deilamsalehy, Xiang Chen, Ruiyi Zhang, Shubham Agarwal, Nedim Lipka, Hamed Zamani. Arxiv 2024.

80. RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering. Rujun Han, Yuhao Zhang, Peng Qi, Yumo Xu, Jenyuan Wang, Lan Liu, William Yang Wang, Bonan Min, Vittorio Castelli. Arxiv 2024.

81. Attention Is All You Need But You Don't Need All Of It For Inference of Large Language Models. Georgy Tyukin, Gbetondji J-S Dovonon, Jean Kaddour, Pasquale Minervini. ICML 2024 TF2M workshop.

82. Stress-Testing Long-Context Language Models with Lifelong ICL and Task Haystack. Xiaoyue Xu, Qinyuan Ye, Xiang Ren. Arxiv 2024.        

83. WildHallucinations: Evaluating Long-form Factuality in LLMs with Real-World Entity Queries. Wenting Zhao, Tanya Goyal, Yu Ying Chiu, Liwei Jiang, Benjamin Newman, Abhilasha Ravichander, Khyathi Chandu, Ronan Le Bras, Claire Cardie, Yuntian Deng, Yejin Choi. Arxiv 2024.

84. Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach. Zhuowan Li, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Michael Bendersky. Arxiv 2024.

85. Evaluating Long Range Dependency Handling in Code Generation Models using Multi-Step Key Retrieval. Yannick Assogba, Donghao Ren. Arxiv 2024.

86. Long Input Benchmark for Russian Analysis. Igor Churin, Murat Apishev, Maria Tikhonova, Denis Shevelev, Aydar Bulatov, Yuri Kuratov, Sergej Averkiev, Alena Fenogenova. Arxiv 2024.

87. CoverBench: A Challenging Benchmark for Complex Claim Verification. Alon Jacovi, Moran Ambar, Eyal Ben-David, Uri Shaham, Amir Feder, Mor Geva, Dror Marcus, Avi Caciularu. Arxiv 2024.

88. LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs. Yushi Bai, Jiajie Zhang, Xin Lv, Linzhi Zheng, Siqi Zhu, Lei Hou, Yuxiao Dong, Jie Tang, Juanzi Li. Arxiv 2024.

89. Multilingual Needle in a Haystack: Investigating Long-Context Behavior of Multilingual Large Language Models. Amey Hengle, Prasoon Bajpai, Soham Dan, Tanmoy Chakraborty. Arxiv 2024.

90. LongGenBench: Benchmarking Long-Form Generation in Long Context LLMs. Yuhao Wu, Ming Shan Hee, Zhiqing Hu, Roy Ka-Wei Lee. Arxiv 2024.

91. What are the Essential Factors in Crafting Effective Long Context Multi-Hop Instruction Datasets? Insights and Best Practices. Zhi Chen, Qiguang Chen, Libo Qin, Qipeng Guo, Haijun Lv, Yicheng Zou, Wanxiang Che, Hang Yan, Kai Chen, Dahua Lin. Arxiv 2024.

92. Retrieval Or Holistic Understanding? Dolce: Differentiate Our Long Context Evaluation Tasks. Zi Yang. Arxiv 2024.

93. A Controlled Study on Long Context Extension and Generalization in LLMs. Yi Lu, Jing Nathan Yan, Songlin Yang, Justin T. Chiu, Siyu Ren, Fei Yuan, Wenting Zhao, Zhiyong Wu, Alexander M. Rush. Arxiv 2024.

94. RAD-Bench: Evaluating Large Language Models Capabilities in Retrieval Augmented Dialogues. Tzu-Lin Kuo, Feng-Ting Liao, Mu-Wei Hsieh, Fu-Chieh Chang, Po-Chun Hsu, Da-Shan Shiu. Arxiv 2024.

95. Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation. Satyapriya Krishna, Kalpesh Krishna, Anhad Mohananey, Steven Schwarcz, Adam Stambler, Shyam Upadhyay, Manaal Faruqui. Arxiv 2024.

96. Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries. Kiran Vodrahalli, Santiago Ontanon, Nilesh Tripuraneni, Kelvin Xu, Sanil Jain, Rakesh Shivanna, Jeffrey Hui, Nishanth Dikkala, Mehran Kazemi, Bahare Fatemi, Rohan Anil, Ethan Dyer, Siamak Shakeri, Roopali Vij, Harsh Mehta, Vinay Ramasesh, Quoc Le, Ed Chi, Yifeng Lu, Orhan Firat, Angeliki Lazaridou, Jean-Baptiste Lespiau, Nithya Attaluri, Kate Olszewska. Arxiv 2024.

97. DetectiveQA: Evaluating Long-Context Reasoning on Detective Novels. Zhe Xu, Jiasheng Ye, Xiangyang Liu, Tianxiang Sun, Xiaoran Liu, Qipeng Guo, Linlin Li, Qun Liu, Xuanjing Huang, Xipeng Qiu. Arxiv 2024.

98. LongCite: Enabling LLMs to Generate Fine-grained Citations in Long-context QA. Jiajie Zhang, Yushi Bai, Xin Lv, Wanjun Gu, Danqing Liu, Minhao Zou, Shulin Cao, Lei Hou, Yuxiao Dong, Ling Feng, Juanzi Li. Arxiv 2024.

99. HelloBench: Evaluating Long Text Generation Capabilities of Large Language Models. Haoran Que, Feiyu Duan, Liqun He, Yutao Mou, Wangchunshu Zhou, Jiaheng Liu, Wenge Rong, Zekun Moore Wang, Jian Yang, Ge Zhang, Junran Peng, Zhaoxiang Zhang, Songyang Zhang, Kai Chen. Arxiv 2024.

100. Multilingual Evaluation of Long Context Retrieval and Reasoning. Ameeta Agrawal, Andy Dang, Sina Bagheri Nezhad, Rhitabrat Pokharel, Russell Scheinberg. Arxiv 2024.

101. L-CiteEval: Do Long-Context Models Truly Leverage Context for Responding? Zecheng Tang, Keyan Zhou, Juntao Li, Baibei Ji, Jianye Hou, Min Zhang. Arxiv 2024.

102. HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly. Howard Yen, Tianyu Gao, Minmin Hou, Ke Ding, Daniel Fleischer, Peter Izasak, Moshe Wasserblat, Danqi Chen. Arxiv 2024.

103. MathHay: An Automated Benchmark for Long-Context Mathematical Reasoning in LLMs. Lei Wang, Shan Dong, Yuhui Xu, Hanze Dong, Yalu Wang, Amrita Saha, Ee-Peng Lim, Caiming Xiong, Doyen Sahoo. Arxiv 2024.

104. LongGenBench: Long-context Generation Benchmark. Xiang Liu, Peijie Dong, Xuming Hu, Xiaowen Chu. EMNLP 2024.

105. Hyper-multi-step: The Truth Behind Difficult Long-context Tasks. Yijiong Yu. Arxiv 2024.

106. Holistic Reasoning with Long-Context LMs: A Benchmark for Database Operations on Massive Textual Data. Seiji Maekawa, Hayate Iso, Nikita Bhutani. Arxiv 2024.

107. How much do contextualized representations encode long-range context?. Simeng Sun, Cheng-Ping Hsieh. Arxiv 2024.

108. LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory. Di Wu, Hongwei Wang, Wenhao Yu, Yuwei Zhang, Kai-Wei Chang, Dong Yu. Arxiv 2024.

109. When Attention Sink Emerges in Language Models: An Empirical View. Xiangming Gu, Tianyu Pang, Chao Du, Qian Liu, Fengzhuo Zhang, Cunxiao Du, Ye Wang, Min Lin. Arxiv 2024.

110. Minimum Tuning to Unlock Long Output from LLMs with High Quality Data as the Key. Yingda Chen, Xingjun Wang, Jintao Huang, Yunlin Mao, Daoze Zhang, Yuze Zhao. Arxiv 2024.

111. Distance between Relevant Information Pieces Causes Bias in Long-Context LLMs. Runchu Tian, Yanghao Li, Yuepeng Fu, Siyang Deng, Qinyu Luo, Cheng Qian, Shuo Wang, Xin Cong, Zhong Zhang, Yesai Wu, Yankai Lin, Huadong Wang, Xiaojiang Liu. Arxiv 2024.

112. ETHIC: Evaluating Large Language Models on Long-Context Tasks with High Information Coverage. Taewhoo Lee, Chanwoong Yoon, Kyochul Jang, Donghyeon Lee, Minju Song, Hyunjae Kim, Jaewoo Kang. Arxiv 2024.

113. Long2RAG: Evaluating Long-Context & Long-Form Retrieval-Augmented Generation with Key Point Recall. Zehan Qi, Rongwu Xu, Zhijiang Guo, Cunxiang Wang, Hao Zhang, Wei Xu. EMNLP 2024.

114. Needle Threading: Can LLMs Follow Threads through Near-Million-Scale Haystacks?. Jonathan Roberts, Kai Han, Samuel Albanie. Arxiv 2024.

115. Retrieval or Global Context Understanding? On Many-Shot In-Context Learning for Long-Context Evaluation. Kaijian Zou, Muhammad Khalifa, Lu Wang. Arxiv 2024.

116. LIFBench: Evaluating the Instruction Following Performance and Stability of Large Language Models in Long-Context Scenarios. Xiaodong Wu, Minhao Wang, Yichen Liu, Xiaoming Shi, He Yan, Xiangju Lu, Junmin Zhu, Wei Zhang. Arxiv 2024.

117. Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows. Fangyu Lei, Jixuan Chen, Yuxiao Ye, Ruisheng Cao, Dongchan Shin, Hongjin Su, Zhaoqing Suo, Hongcheng Gao, Wenjing Hu, Pengcheng Yin, Victor Zhong, Caiming Xiong, Ruoxi Sun, Qian Liu, Sida Wang, Tao Yu. Arxiv 2024.        

118. A Benchmark for Long-Form Medical Question Answering. Pedram Hosseini, Jessica M. Sin, Bing Ren, Bryceton G. Thomas, Elnaz Nouri, Ali Farahanchi, Saeed Hassanpour. NeurIPS 2024.

119. DENIAHL: In-Context Features Influence LLM Needle-In-A-Haystack Abilities. Hui Dai, Dan Pechi, Xinyi Yang, Garvit Banga, Raghav Mantri. Arxiv 2024.

120. LCFO: Long Context and Long Form Output Dataset and Benchmarking. Marta R. Costa-jussà, Pierre Andrews, Mariano Coria Meglioli, Joy Chen, Joe Chuang, David Dale, Christophe Ropers, Alexandre Mourachko, Eduardo Sánchez, Holger Schwenk, Tuan Tran, Arina Turkatenko, Carleigh Wood. Arxiv 2024.

121. SCBench: A KV Cache-Centric Analysis of Long-Context Methods. Yucheng Li, Huiqiang Jiang, Qianhui Wu, Xufang Luo, Surin Ahn, Chengruidong Zhang, Amir H. Abdi, Dongsheng Li, Jianfeng Gao, Yuqing Yang, Lili Qiu. Arxiv 2024.

122. LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks. Yushi Bai, Shangqing Tu, Jiajie Zhang, Hao Peng, Xiaozhi Wang, Xin Lv, Shulin Cao, Jiazheng Xu, Lei Hou, Yuxiao Dong, Jie Tang, Juanzi Li. Arxiv 2024.

123. XRAG: eXamining the Core -- Benchmarking Foundational Components in Advanced Retrieval-Augmented Generation. Qianren Mao, Yangyifei Luo, Jinlong Zhang, Hanwen Hao, Zhilong Cao, Xiaolong Wang, Xiao Guan, Zhenting Huang, Weifeng Jiang, Shuyu Guo, Zhentao Han, Qili Zhang, Siyuan Tao, Yujie Liu, Junnan Liu, Zhixing Tan, Jie Sun, Bo Li, Xudong Liu, Richong Zhang, Jianxin Li. Arxiv 2024.

124. RepoTransBench: A Real-World Benchmark for Repository-Level Code Translation. Yanli Wang, Yanlin Wang, Suiquan Wang, Daya Guo, Jiachi Chen, John Grundy, Xilin Liu, Yuchi Ma, Mingzhi Mao, Hongyu Zhang, Zibin Zheng. Arxiv 2024.

125. Long Context vs. RAG for LLMs: An Evaluation and Revisits. Xinze Li, Yixin Cao, Yubo Ma, Aixin Sun. Arxiv 2025.

126. The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input. Alon Jacovi, Andrew Wang, Chris Alberti, Connie Tao, Jon Lipovetz, Kate Olszewska, Lukas Haas, Michelle Liu, Nate Keating, Adam Bloniarz, Carl Saroufim, Corey Fry, Dror Marcus, Doron Kukliansky, Gaurav Singh Tomar, James Swirhun, Jinwei Xing, Lily Wang, Madhu Gurumurthy, Michael Aaron, Moran Ambar, Rachana Fellinger, Rui Wang, Zizhao Zhang, Sasha Goldshtein, Dipanjan Das. Arxiv 2025.

127. MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems. Yannis Katsis, Sara Rosenthal, Kshitij Fadnis, Chulaka Gunasekara, Young-Suk Lee, Lucian Popa, Vraj Shah, Huaiyu Zhu, Danish Contractor, Marina Danilevsky. Arxiv 2025.

128. ComplexFuncBench: Exploring Multi-Step and Constrained Function Calling under Long-Context Scenario. Lucen Zhong, Zhengxiao Du, Xiaohan Zhang, Haiyi Hu, Jie Tang. Arxiv 2025.

129. RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?. Haotian Xu, Xing Wu, Weinong Wang, Zhongzhi Li, Da Zheng, Boyuan Chen, Yi Hu, Shijia Kang, Jiaming Ji, Yingying Zhang, Zhijiang Guo, Yaodong Yang, Muhan Zhang, Debing Zhang. Arxiv 2025.

130. LongReason: A Synthetic Long-Context Reasoning Benchmark via Context Expansion. Zhan Ling, Kang Liu, Kai Yan, Yifan Yang, Weijian Lin, Ting-Han Fan, Lingfeng Shen, Zhengyin Du, Jiecao Chen. Arxiv 2025.

131. Explaining Context Length Scaling and Bounds for Language Models. Jingzhe Shi, Qinwei Ma, Hongyi Liu, Hang Zhao, Jeng-Neng Hwang, Serge Belongie, Lei Li. Arxiv 2025.

132. Attention Sinks and Outlier Features: A 'Catch, Tag, and Release' Mechanism for Embeddings. Stephen Zhang, Mustafa Khan, Vardan Papyan. Arxiv 2025.

133. Demystifying Long Chain-of-Thought Reasoning in LLMs. Edward Yeo, Yuxuan Tong, Morry Niu, Graham Neubig, Xiang Yue. Arxiv 2025.

134. BOLT: Bootstrap Long Chain-of-Thought in Language Models without Distillation. Bo Pang, Hanze Dong, Jiacheng Xu, Silvio Savarese, Yingbo Zhou, Caiming Xiong. Arxiv 2025.

135. NoLiMa: Long-Context Evaluation Beyond Literal Matching. Ali Modarressi, Hanieh Deilamsalehy, Franck Dernoncourt, Trung Bui, Ryan A. Rossi, Seunghyun Yoon, Hinrich Schütze. Arxiv 2025.

136. Technical Debt in In-Context Learning: Diminishing Efficiency in Long Context. Taejong Joo, Diego Klabjan. Arxiv 2025.

137. Demystifying Long Chain-of-Thought Reasoning in LLMs. Edward Yeo, Yuxuan Tong, Morry Niu, Graham Neubig, Xiang Yue. Arxiv 2025.        

138. DebateBench: A Challenging Long Context Reasoning Benchmark For Large Language Models. Utkarsh Tiwari, Aryan Seth, Adi Mukherjee, Kaavya Mer, Kavish, Dhruv Kumar. Arxiv 2025.

139. CLOVER: A Test Case Generation Benchmark with Coverage, Long-Context, and Verification. Jiacheng Xu, Bo Pang, Jin Qu, Hiroaki Hayashi, Caiming Xiong, Yingbo Zhou. Arxiv 2025.

140. MIR-Bench: Benchmarking LLM's Long-Context Intelligence via Many-Shot In-Context Inductive Reasoning. Kai Yan, Zhan Ling, Kang Liu, Yifan Yang, Ting-Han Fan, Lingfeng Shen, Zhengyin Du, Jiecao Chen. Arxiv 2025.

141. LaRA: Benchmarking Retrieval-Augmented Generation and Long-Context LLMs - No Silver Bullet for LC or RAG Routing. Kuan Li, Liwen Zhang, Yong Jiang, Pengjun Xie, Fei Huang, Shuai Wang, Minhao Cheng. Arxiv 2025.

142. Does RAG Really Perform Bad For Long-Context Processing?. Kun Luo, Zheng Liu, Peitian Zhang, Hongjin Qian, Jun Zhao, Kang Liu. Arxiv 2025.

143. SQLong: Enhanced NL2SQL for Longer Contexts with LLMs. Dai Quoc Nguyen, Cong Duy Vu Hoang, Duy Vu, Gioacchino Tangari, Thanh Tien Vu, Don Dharmasiri, Yuan-Fang Li, Long Duong. Arxiv 2025.

144. LongSafety: Evaluating Long-Context Safety of Large Language Models. Yida Lu, Jiale Cheng, Zhexin Zhang, Shiyao Cui, Cunxiang Wang, Xiaotao Gu, Yuxiao Dong, Jie Tang, Hongning Wang, Minlie Huang. Arxiv 2025.

145. LR2Bench: Evaluating Long-chain Reflective Reasoning Capabilities of Large Language Models via Constraint Satisfaction Problems. Jianghao Chen, Zhenlin Wei, Zhenjiang Ren, Ziyong Li, Jiajun Zhang. Arxiv 2025.

146. DocPuzzle: A Process-Aware Benchmark for Evaluating Realistic Long-Context Reasoning Capabilities. Tianyi Zhuang, Chuqiao Kuang, Xiaoguang Li, Yihua Teng, Jihao Wu, Yasheng Wang, Lifeng Shang. Arxiv 2025.

147. Chain-of-Thought Matters: Improving Long-Context Language Models with Reasoning Path Supervision. Dawei Zhu, Xiyu Wei, Guangxiang Zhao, Wenhao Wu, Haosheng Zou, Junfeng Ran, Xun Wang, Lin Sun, Xiangzheng Zhang, Sujian Li. Arxiv 2025.

148. U-NIAH: Unified RAG and LLM Evaluation for Long Context Needle-In-A-Haystack. Yunfan Gao, Yun Xiong, Wenlong Wu, Zijing Huang, Bohan Li, Haofen WangYunfan Gao, Yun Xiong, Wenlong Wu, Zijing Huang, Bohan Li, Haofen Wang. Arxiv 2025.

149. L2M: Mutual Information Scaling Law for Long-Context Language Modeling. Zhuo Chen, Oriol Mayné i Comas, Zhuotao Jin, Di Luo, Marin Soljačić. Arxiv 2025.

150. CURIE: Evaluating LLMs On Multitask Scientific Long Context Understanding and Reasoning. Hao Cui, Zahra Shamsi, Gowoon Cheon, Xuejian Ma, Shutong Li, Maria Tikhanovskaya, Peter Norgaard, Nayantara Mudur, Martyna Plomecka, Paul Raccuglia, Yasaman Bahri, Victor V. Albert, Pranesh Srinivasan, Haining Pan, Philippe Faist, Brian Rohr, Michael J. Statt, Dan Morris, Drew Purves, Elise Kleeman, Ruth Alcantara, Matthew Abraham, Muqthar Mohammad, Ean Phing VanLee, Chenfei Jiang, Elizabeth Dorfman, Eun-Ah Kim, Michael P Brenner, Viren Jain, Sameera Ponda, Subhashini Venugopalan. Arxiv 2025.

151. Can LLMs reason over extended multilingual contexts? Towards long-context evaluation beyond retrieval and haystacks. Amey Hengle, Prasoon Bajpai, Soham Dan, Tanmoy Chakraborty. Arxiv 2025.

152. Too Long, Didn't Model: Decomposing LLM Long-Context Understanding With Novels. Sil Hamilton, Rebecca M. M. Hicke, Matthew Wilkens, David MimnoSil Hamilton, Rebecca M. M. Hicke, Matthew Wilkens, David Mimno. Arxiv 2025.

153. Longer Context, Deeper Thinking: Uncovering the Role of Long-Context Ability in Reasoning. Wang Yang, Zirui Liu, Hongye Jin, Qingyu Yin, Vipin Chaudhary, Xiaotian Han. Arxiv 2025.

154. Does quantization affect models' performance on long-context tasks?. Anmol Mekala, Anirudh Atmakuru, Yixiao Song, Marzena Karpinska, Mohit Iyyer. Arxiv 2025.

155. SwingArena: Competitive Programming Arena for Long-context GitHub Issue Solving. Wendong Xu, Jing Xiong, Chenyang Zhao, Qiujiang Chen, Haoran Wang, Hui Shen, Zhongwei Wan, Jianbo Dai, Taiqiang Wu, He Xiao, Chaofan Tao, Z. Morley Mao, Ying Sheng, Zhijiang Guo, Hongxia Yang, Bei Yu, Lingpeng Kong, Quanquan Gu, Ngai Wong._ Arxiv 2025.

156. THINK-Bench: Evaluating Thinking Efficiency and Chain-of-Thought Quality of Large Reasoning Models. Zhiyuan Li, Yi Chang, Yuan Wu. Arxiv 2025.

157. MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models. Zhongzhan Huang, Guoming Ling, Shanshan Zhong, Hefeng Wu, Liang Lin. ACL 2025.

158. 100-LongBench: Are de facto Long-Context Benchmarks Literally Evaluating Long-Context Ability?. Wang Yang, Hongye Jin, Shaochen Zhong, Song Jiang, Qifan Wang, Vipin Chaudhary, Xiaotian Han. Arxiv 2025.

159. ExpertLongBench: Benchmarking Language Models on Expert-Level Long-Form Generation Tasks with Structured Checklists. Jie Ruan, Inderjeet Nair, Shuyang Cao, Amy Liu, Sheza Munir, Micah Pollens-Dempsey, Tiffany Chiang, Lucy Kates, Nicholas David, Sihan Chen, Ruxin Yang, Yuqian Yang, Jasmine Gump, Tessa Bialek, Vivek Sankaran, Margo Schlanger, Lu Wang. Arxiv 2025.

160. Dissecting Long Reasoning Models: An Empirical Study. Yongyu Mu, Jiali Zeng, Bei Li, Xinyan Guan, Fandong Meng, Jie Zhou, Tong Xiao, Jingbo Zhu. Arxiv 2025.

161. LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework. Zecheng Tang, Haitian Wang, Quantong Qiu, Baibei Ji, Ruoxi Sun, Keyan Zhou, Juntao Li, Min Zhang. Arxiv 2025.        

162. LLMThinkBench: Towards Basic Math Reasoning and Overthinking in Large Language Models. Gaurav Srivastava, Aafiya Hussain, Sriram Srinivasan, Xuan Wang. Arxiv 2025.

163. NeedleChain: Measuring Intact Long-Context Reasoning Capability of Large Language Models. Hyeonseok Moon, Heuiseok Lim. Arxiv 2025.

164. PRELUDE: A Benchmark Designed to Require Global Comprehension and Reasoning over Long Contexts. Mo Yu, Tsz Ting Chung, Chulun Zhou, Tong Li, Rui Lu, Jiangnan Li, Liyan Xu, Haoshu Lu, Ning Zhang, Jing Li, Jie Zhou. Arxiv 2025.

165. OptimalThinkingBench: Evaluating Over and Underthinking in LLMs. Pranjal Aggarwal, Seungone Kim, Jack Lanchantin, Sean Welleck, Jason Weston, Ilia Kulikov, Swarnadeep Saha. Arxiv 2025.

166. LongReasonArena: A Long Reasoning Benchmark for Large Language Models. Jiayu Ding, Shuming Ma, Lei Cui, Nanning Zheng, Furu Wei. Arxiv 2025.

167. UltraHorizon: Benchmarking Agent Capabilities in Ultra Long-Horizon Scenarios. Haotian Luo, Kaijiang Pan, Bosheng Qin, Yijun Wang, Yubai Yuan, Chufeng Tang, Zhongyi Li, Lei Chen, Wenqi Shao, Yao Teng, Yongqi Zhang, Yuhui Yuan, Maosong Sun, Li Shen. Arxiv 2025.

168. A Controllable Examination for Long-Context Language Models Yijun Yang, Zeyu Huang, Wenhao Zhu, Zihan Qiu, Fei Yuan, Jeff Z.Pan, Ivan Titov. NeurIPS 2025 Spotlight.

11.2 MLLM

1. MileBench: Benchmarking MLLMs in Long Context. Dingjie Song, Shunian Chen, Guiming Hardy Chen, Fei Yu, Xiang Wan, Benyou Wang. Arxiv 2024.

2. Many-Shot In-Context Learning in Multimodal Foundation Models. Yixing Jiang, Jeremy Irvin, Ji Hun Wang, Muhammad Ahmed Chaudhry, Jonathan H. Chen, Andrew Y. Ng. Arxiv 2024.

3. MLVU: A Comprehensive Benchmark for Multi-Task Long Video Understanding. Junjie Zhou, Yan Shu, Bo Zhao, Boya Wu, Shitao Xiao, Xi Yang, Yongping Xiong, Bo Zhang, Tiejun Huang, Zheng Liu. Arxiv 2024.

4. RepoQA: Evaluating Long Context Code Understanding. Jiawei Liu, Jia Le Tian, Vijay Daita, Yuxiang Wei, Yifeng Ding, Yuhan Katherine Wang, Jun Yang, Lingming Zhang. Arxiv 2024.        

5. Short Film Dataset (SFD): A Benchmark for Story-Level Video Understanding. Ridouane Ghermi, Xi Wang, Vicky Kalogeiton, Ivan Laptev. Arxiv 2024.        

6. Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models. Hengyi Wang, Haizhou Shi, Shiwei Tan, Weiyi Qin, Wenyuan Wang, Tunyu Zhang, Akshay Nambi, Tanuja Ganu, Hao Wang. Arxiv 2024.

7. Losing Visual Needles in Image Haystacks: Vision Language Models are Easily Distracted in Short and Long Contexts. Aditya Sharma, Michael Saxon, William Yang Wang. Arxiv 2024.

8. MMLongBench-Doc: Benchmarking Long-context Document Understanding with Visualizations. Yubo Ma, Yuhang Zang, Liangyu Chen, Meiqi Chen, Yizhu Jiao, Xinze Li, Xinyuan Lu, Ziyu Liu, Yan Ma, Xiaoyi Dong, Pan Zhang, Liangming Pan, Yu-Gang Jiang, Jiaqi Wang, Yixin Cao, Aixin Sun. Arxiv 2024.        

9. InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output. Pan Zhang, Xiaoyi Dong, Yuhang Zang, Yuhang Cao, Rui Qian, Lin Chen, Qipeng Guo, Haodong Duan, Bin Wang, Linke Ouyang, Songyang Zhang, Wenwei Zhang, Yining Li, Yang Gao, Peng Sun, Xinyue Zhang, Wei Li, Jingwen Li, Wenhai Wang, Hang Yan, Conghui He, Xingcheng Zhang, Kai Chen, Jifeng Dai, Yu Qiao, Dahua Lin, Jiaqi Wang. Arxiv 2024.

10. Stark: Social Long-Term Multi-Modal Conversation with Persona Commonsense Knowledge. Young-Jun Lee, Dokyong Lee, Junyoung Youn, Kyeongjin Oh, Byungsoo Ko, Jonghwan Hyeon, Ho-Jin Choi. Arxiv 2024.        

11. SPIQA: A Dataset for Multimodal Question Answering on Scientific Papers. Shraman Pramanick, Rama Chellappa, Subhashini Venugopalan. Arxiv 2024.

12. LongVideoBench: A Benchmark for Long-context Interleaved Video-Language Understanding. Haoning Wu, Dongxu Li, Bei Chen, Junnan Li. Arxiv 2024.        

13. mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval. Xin Zhang, Yanzhao Zhang, Dingkun Long, Wen Xie, Ziqi Dai, Jialong Tang, Huan Lin, Baosong Yang, Pengjun Xie, Fei Huang, Meishan Zhang, Wenjie Li, Min Zhang. Arxiv 2024.

14. MovieSum: An Abstractive Summarization Dataset for Movie Screenplays. Rohit Saxena, Frank Keller. Arxiv 2024.

15. SEED-Story: Multimodal Long Story Generation with Large Language Model. Shuai Yang, Yuying Ge, Yang Li, Yukang Chen, Yixiao Ge, Ying Shan, Yingcong Chen. Arxiv 2024.

16. M-Longdoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework. Yew Ken Chia, Liying Cheng, Hou Pong Chan, Chaoqun Liu, Maojia Song, Sharifah Mahani Aljunied, Soujanya Poria, Lidong Bing. Arxiv 2024.

17. LongVALE: Vision-Audio-Language-Event Benchmark Towards Time-Aware Omni-Modal Perception of Long Videos. Tiantian Geng, Jinrui Zhang, Qingni Wang, Teng Wang, Jinming Duan, Feng Zheng. Arxiv 2024.

18. LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations. Anian Ruoss, Fabio Pardo, Harris Chan, Bonnie Li, Volodymyr Mnih, Tim Genewein. Arxiv 2024.

19. Neptune: The Long Orbit to Benchmarking Long Video Understanding. Arsha Nagrani, Mingda Zhang, Ramin Mehran, Rachel Hornung, Nitesh Bharadwaj Gundavarapu, Nilpa Jha, Austin Myers, Xingyi Zhou, Boqing Gong, Cordelia Schmid, Mikhail Sirotenko, Yukun Zhu, Tobias Weyand. Arxiv 2024.

20. VisDoM: Multi-Document QA with Visually Rich Elements Using Multimodal Retrieval-Augmented Generation. Manan Suri, Puneet Mathur, Franck Dernoncourt, Kanika Goswami, Ryan A. Rossi, Dinesh Manocha. Arxiv 2024.

21. Is Your World Simulator a Good Story Presenter? A Consecutive Events-Based Benchmark for Future Long Video Generation. Yiping Wang, Xuehai He, Kuan Wang, Luyao Ma, Jianwei Yang, Shuohang Wang, Simon Shaolei Du, Yelong Shen. Arxiv 2024.        

22. LongDocURL: a Comprehensive Multimodal Long Document Benchmark Integrating Understanding, Reasoning, and Locating. Chao Deng, Jiale Yuan, Pi Bu, Peijie Wang, Zhong-Zhi Li, Jian Xu, Xiao-Hui Li, Yuan Gao, Jun Song, Bo Zheng, Cheng-Lin Liu. Arxiv 2024.

23. HLV-1K: A Large-scale Hour-Long Video Benchmark for Time-Specific Long Video Understanding. Heqing Zou, Tianze Luo, Guiyang Xie, Victor (Xiao Jie)Zhang, Fengmao Lv, Guangcong Wang, Junyang Chen, Zhuochen Wang, Hansheng Zhang, Huaijian Zhang. Arxiv 2025.

24. MMDocIR: Benchmarking Multi-Modal Retrieval for Long Documents. Kuicai Dong, Yujing Chang, Xin Deik Goh, Dexun Li, Ruiming Tang, Yong Liu. Arxiv 2025.

25. EnigmaEval: A Benchmark of Long Multimodal Reasoning Challenges. Clinton J. Wang, Dean Lee, Cristina Menghini, Johannes Mols, Jack Doughty, Adam Khoja, Jayson Lynch, Sean Hendryx, Summer Yue, Dan Hendrycks. Arxiv 2025.

26. MomentSeeker: A Comprehensive Benchmark and A Strong Baseline For Moment Retrieval Within Long Videos. Huaying Yuan, Jian Ni, Yueze Wang, Junjie Zhou, Zhengyang Liang, Zheng Liu, Zhao Cao, Zhicheng Dou, Ji-Rong Wen. Arxiv 2025.

27. Compression Scaling Laws:Unifying Sparsity and Quantization. Elias Frantar, Utku Evci, Wonpyo Park, Neil Houlsby, Dan Alistarh. Arxiv 2025.

28. One ruler to measure them all: Benchmarking multilingual long-context language models. Yekyung Kim, Jenna Russell, Marzena Karpinska, Mohit Iyyer. Arxiv 2025.

29. LVLM-Compress-Bench: Benchmarking the Broader Impact of Large Vision-Language Model Compression. Souvik Kundu, Anahita Bhiwandiwalla, Sungduk Yu, Phillip Howard, Tiep Le, Sharath Nittur Sridhar, David Cobbley, Hao Kang, Vasudev Lal. NAACL 2025.

30. NeedleInATable: Exploring Long-Context Capability of Large Language Models towards Long-Structured Tables. Lanrui Wang, Mingyu Zheng, Hongyin Tang, Zheng Lin, Yanan Cao, Jingang Wang, Xunliang Cai, Weiping Wang. Arxiv 2025.

31. LiveLongBench: Tackling Long-Context Understanding for Spoken Texts from Live Streams. Yongxuan Wu, Runyu Chen, Peiyu Liu, Hongjin Qian. Arxiv 2025.

32. MMLongBench: Benchmarking Long-Context Vision-Language Models Effectively and Thoroughly. Zhaowei Wang, Wenhao Yu, Xiyu Ren, Jipeng Zhang, Yu Zhao, Rohit Saxena, Liang Cheng, Ginny Wong, Simon See, Pasquale Minervini, Yangqiu Song, Mark Steedman. Arxiv 2025.

33. ScaleLong: A Multi-Timescale Benchmark for Long Video Understanding. David Ma, Huaqing Yuan, Xingjian Wang, Qianbo Zang, Tianci Liu, Xinyang He, Yanbin Wei, Jiawei Guo, Ni Jiahui, Zhenzhu Yang, Meng Cao, Shanghaoran Quan, Yizhi Li, Wangchunshu Zhou, Jiaheng Liu, Wenhao Huang, Ge Zhang, Shiwen Ni, Xiaojie Jin. Arxiv 2025.

34. LVBench: An Extreme Long Video Understanding Benchmark. Weihan Wang, Zehai He, Wenyi Hong, Yean Cheng, Xiaohan Zhang, Ji Qi, Xiaotao Gu, Shiyu Huang, Bin Xu, Yuxiao Dong, Ming Ding, Jie Tang. ICCV 2025.

35. MMLongCite: A Benchmark for Evaluating Fidelity of Long-Context Vision-Language Models. Keyan Zhou, Zecheng Tang, Lingfeng Ming, Guanghao Zhou, Qiguang Chen, Dan Qiao, Zheming Yang, Libo Qin, Minghui Qiu, Juntao Li, Min Zhang. Arxiv 2025.

11.3 Agentic

1. Watching, Reasoning, and Searching: A Video Deep Research Benchmark on Open Web for Agentic Video Reasoning. Chengwen Liu, Xiaomin Yu, Zhuoyue Chang, Zhe Huang, Shuo Zhang, Heng Lian, Kunyi Wang, Rui Xu, Sen Hu, Jianheng Hou, Hao Peng, Chengwei Qin, Xiaobin Hu, Hong Peng, Ronghao Chen, Huacan Wang. Arxiv 2026.

12. Long Text Generation

1. Integrating Planning into Single-Turn Long-Form Text Generation. Yi Liang, You Wu, Honglei Zhuang, Li Chen, Jiaming Shen, Yiling Jia, Zhen Qin, Sumit Sanghai, Xuanhui Wang, Carl Yang, Michael Bendersky. Arxiv 2024.

2. Minimum Tuning to Unlock Long Output from LLMs with High Quality Data as the Key. Yingda Chen, Xingjun Wang, Jintao Huang, Yunlin Mao, Daoze Zhang, Yuze Zhao. Arxiv 2024.

3. LongGenBench: Long-context Generation Benchmark. Xiang Liu, Peijie Dong, Xuming Hu, Xiaowen Chu. EMNLP 2024.

4. LoGU: Long-form Generation with Uncertainty Expressions. Ruihan Yang, Caiqi Zhang, Zhisong Zhang, Xinting Huang, Sen Yang, Nigel Collier, Dong Yu, Deqing Yang. Arxiv 2024.

5. Large Language Models Still Exhibit Bias in Long Text. Wonje Jeung, Dongjae Jeon, Ashkan Yousefpour, Jonghyun Choi. Arxiv 2024.

6. Suri: Multi-constraint Instruction Following for Long-form Text Generation. Chau Minh Pham, Simeng Sun, Mohit Iyyer. Arxiv 2024.

7. LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs. Yushi Bai, Jiajie Zhang, Xin Lv, Linzhi Zheng, Siqi Zhu, Lei Hou, Yuxiao Dong, Jie Tang, Juanzi Li. Arxiv 2024.

8. Language Models can Self-Lengthen to Generate Long Texts. Shanghaoran Quan, Tianyi Tang, Bowen Yu, An Yang, Dayiheng Liu, Bofei Gao, Jianhong Tu, Yichang Zhang, Jingren Zhou, Junyang Lin. Arxiv 2024.

9. Generating Long-form Story Using Dynamic Hierarchical Outlining with Memory-Enhancement. Qianyue Wang, Jinwu Hu, Zhengping Li, Yufeng Wang, daiyuan li, Yu Hu, Mingkui Tan. Arxiv 2024.

10. Beyond Factual Accuracy: Evaluating Coverage of Diverse Factual Information in Long-form Text Generation. Chris Samarinas, Alexander Krubner, Alireza Salemi, Youngwoo Kim, Hamed Zamani. Arxiv 2025.

11. The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input. Alon Jacovi, Andrew Wang, Chris Alberti, Connie Tao, Jon Lipovetz, Kate Olszewska, Lukas Haas, Michelle Liu, Nate Keating, Adam Bloniarz, Carl Saroufim, Corey Fry, Dror Marcus, Doron Kukliansky, Gaurav Singh Tomar, James Swirhun, Jinwei Xing, Lily Wang, Madhu Gurumurthy, Michael Aaron, Moran Ambar, Rachana Fellinger, Rui Wang, Zizhao Zhang, Sasha Goldshtein, Dipanjan Das. Arxiv 2025.

12. LongProc: Benchmarking Long-Context Language Models on Long Procedural Generation. Xi Ye, Fangcong Yin, Yinghui He, Joie Zhang, Howard Yen, Tianyu Gao, Greg Durrett, Danqi Chen. Arxiv 2025.        

13. ExPerT: Effective and Explainable Evaluation of Personalized Long-Form Text Generation. Alireza Salemi, Julian Killingback, Hamed Zamani. Arxiv 2025.

14. LongDPO: Unlock Better Long-form Generation Abilities for LLMs via Critique-augmented Stepwise Information. Bowen Ping, Jiali Zeng, Fandong Meng, Shuo Wang, Jie Zhou, Shanghang Zhang. Arxiv 2025.

15. Context-Preserving Gradient Modulation for Large Language Models: A Novel Approach to Semantic Consistency in Long-Form Text Generation. Nirola Kobanov, Edmund Weatherstone, Zachary Vanderpoel, Orlando Wetherby. Arxiv 2025.

16. A Cognitive Writing Perspective for Constrained Long-Form Text Generation. Kaiyang Wan, Honglin Mu, Rui Hao, Haoran Luo, Tianle Gu, Xiuying Chen. Arxiv 2025.

17. CLIPPER: Compression enables long-context synthetic data generation. Chau Minh Pham, Yapei Chang, Mohit Iyyer. Arxiv 2025.

18. LongWriter-V: Enabling Ultra-Long and High-Fidelity Generation in Vision-Language Models. Shangqing Tu, Yucheng Wang, Daniel Zhang-Li, Yushi Bai, Jifan Yu, Yuhao Wu, Lei Hou, Huiqin Liu, Zhiyuan Liu, Bin Xu, Juanzi Li. Arxiv 2025.

19. LongEval: A Comprehensive Analysis of Long-Text Generation Through a Plan-based Paradigm. Siwei Wu, Yizhi Li, Xingwei Qu, Rishi Ravikumar, Yucheng Li, Tyler Loakman Shanghaoran Quan Xiaoyong Wei, Riza Batista-Navarro, Chenghua Lin. Arxiv 2025.

20. From Hours to Minutes: Lossless Acceleration of Ultra Long Sequence Generation up to 100K Tokens. Tong Wu, Junzhe Shen, Zixia Jia, Yuxuan Wang, Zilong Zheng. Arxiv 2025.

21. RAPID: Efficient Retrieval-Augmented Long Text Generation with Writing Planning and Information Discovery. Hongchao Gu, Dexun Li, Kuicai Dong, Hao Zhang, Hang Lv, Hao Wang, Defu Lian, Yong Liu, Enhong Chen. Arxiv 2025.

22. DeFine: A Decomposed and Fine-Grained Annotated Dataset for Long-form Article Generation. Ming Wang, Fang Wang, Minghao Hu, Li He, Haiyang Wang, Jun Zhang, Tianwei Yan, Li Li, Zhunchen Luo, Wei Luo, Xiaoying Bai, Guotong Geng. Arxiv 2025.

23. Lost-in-the-Middle in Long-Text Generation: Synthetic Dataset, Evaluation Framework, and Mitigation. Junhao Zhang, Richong Zhang, Fanshuang Kong, Ziyang Miao, Yanhan Ye, Yaowei Zheng. Arxiv 2025.

24. Beyond Outlining: Heterogeneous Recursive Planning for Adaptive Long-form Writing with Language Models. Ruibin Xiong, Yimeng Chen, Dmitrii Khizbullin, Jürgen Schmidhuber. Arxiv 2025.

25. Learning to Reason for Long-Form Story Generation. Alexander Gurung, Mirella Lapata. Arxiv 2025.

26. ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning. Bairu Hou, Yang Zhang, Jiabao Ji, Yujian Liu, Kaizhi Qian, Jacob Andreas, Shiyu Chang. Arxiv 2025.

27. Think When You Need: Self-Adaptive Chain-of-Thought Learning. Junjie Yang, Ke Lin, Xing Yu. Arxiv 2025.

28. LLM×MapReduce-V2: Entropy-Driven Convolutional Test-Time Scaling for Generating Long-Form Articles from Extremely Long Resources. Haoyu Wang, Yujia Fu, Zhu Zhang, Shuo Wang, Zirui Ren, Xiaorong Wang, Zhili Li, Chaoqun He, Bo An, Zhiyuan Liu, Maosong Sun. Arxiv 2025.

29. SuperWriter: Reflection-Driven Long-Form Generation with Large Language Models. Yuhao Wu, Yushi Bai, Zhiqiang Hu, Juanzi Li, Roy Ka-Wei Lee. Arxiv 2025.

30. Writing-RL: Advancing Long-form Writing via Adaptive Curriculum Reinforcement Learning. Xuanyu Lei, Chenliang Li, Yuning Wu, Kaiming Liu, Weizhou Shen, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Yang Liu. Arxiv 2025.

31. From General to Targeted Rewards: Surpassing GPT-4 in Open-Ended Long-Context Generation. Zhihan Guo, Jiele Wu, Wenqian Cui, Yifei Zhang, Minda Hu, Yufei Wang, Irwin King. Arxiv 2025.

32. StoryWriter: A Multi-Agent Framework for Long Story Generation. Haotian Xia, Hao Peng, Yunjia Qi, Xiaozhi Wang, Bin Xu, Lei Hou, Juanzi Li. Arxiv 2025.

33. LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement Learning. Yuhao Wu, Yushi Bai, Zhiqiang Hu, Roy Ka-Wei Lee, Juanzi Li. Arxiv 2025.

34. ACE-RL: Adaptive Constraint-Enhanced Reward for Long-form Generation Reinforcement Learning. Jianghao Chen, Wei Sun, Qixiang Yin, Lingxing Kong, Zhixing Tan, Jiajun Zhang. Arxiv 2025.

35. LiteLong: Resource-Efficient Long-Context Data Synthesis for LLMs. Junlong Jia, Xing Wu, Chaochen Gao, Ziyang Chen, Zijia Lin, Zhongzhi Li, Weinong Wang, Haotian Xu, Donghui Jin, Debing Zhang, Binghui Guo. Arxiv 2025.