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Paper

LLMCad: Fast and Scalable On-device Large Language Model Inference

by Independent / Community 00e889fcfaf4396a20f37f681cf8b14f3e878879

Free2AITools Nexus Index

69.6

S: Semantic 50

Query-time baseline · scored live at search

A: Authority 85

P: Popularity 62

R: Recency 100

Q: Quality 65

Tech Context

Vital Performance —

Generative tasks, such as text generation and question answering, hold a crucial position in the realm of mobile applications. Due to their sensitivity to privacy concerns, there is a growing demand for their execution directly on mobile devices. Currently, the execution of these generative tasks heavily depends on Large Language Models (LLMs). Nevertheless, the limited memory capacity of these devices presents a formidable challenge to the scalability of such models. In our research, we intr...

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Semantic Scholar 74 Citations

Paper Information Summary
Entity Passport
Registry ID	00e889fcfaf4396a20f37f681cf8b14f3e878879
License	ArXiv
Provider	semantic_scholar

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Cite this paper

Academic & Research Attribution

BibTeX

@misc{00e889fcfaf4396a20f37f681cf8b14f3e878879,
  author = {Unknown},
  title = {LLMCad: Fast and Scalable On-device Large Language Model Inference Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/00e889fcfaf4396a20f37f681cf8b14f3e878879}},
  note = {Accessed via Free2AITools.}
}

APA Style

Unknown. (2026). LLMCad: Fast and Scalable On-device Large Language Model Inference [Paper]. Free2AITools. https://api.semanticscholar.org/00e889fcfaf4396a20f37f681cf8b14f3e878879

🔬Technical Deep Dive

Full Specifications [+]

⚖️ Free2AITools Nexus Index V2.0

Methodology How FNI works

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 85

Popularity (P) 62

Recency (R) 100

Quality (Q) 65

💬 Index Insight

FNI V2.0 for LLMCad: Fast and Scalable On-device Large Language Model Inference: Authority (A:85), Popularity (P:62), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology

Open data Updated: Live data

📝 Executive Summary

"Generative tasks, such as text generation and question answering, hold a crucial position in the realm of mobile applications. Due to their sensitivity to privacy concerns, there is a growing demand for their execution directly on mobile devices. Currently, the execution of these generative tasks heavily depends on Large Language Models (LLMs). Nevertheless, the limited memory capacity of these devices presents a formidable challenge to the scalability of such models. In our research, we intr..."

❝ Cite Node

@article{Unknown2026LLMCad:,
  title={LLMCad: Fast and Scalable On-device Large Language Model Inference},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

🔗 Full Paper

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📊 Research Signals

📈74CitationsSemantic Scholar

🏛️85AuthorityFNI pillar

⏱️100RecencyFNI pillar

✅65QualityFNI pillar

🗂️infrastructure opsField

📦Data Source: semantic_scholar

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🆔 Identity & Source

source: semantic_scholar
author: Unknown
license: ArXiv
tags: paper, research, academic

⚙️ Technical Specs

architecture: null
params billions: null
context length: null
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downloads: 0
stars: null
forks: null
citations: 74

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