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Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models paper
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Paper

Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models

001cca7910f507f7f75b8402b826c2dc07afef00
Free2AITools Nexus Index
70.0
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 87
P: Popularity 64
R: Recency 100
Q: Quality 65
Tech Context
Vital Performance —

The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated models like OpenAI’s ChatGPT, represents a significant advancement in artificial intelligence. These models, however, bring forth substantial challenges in high consumption of computational, memory, energy, and financial resources, especially in environments with limited resource capabilities. This survey aims to systematically address these challenges by reviewing a broad spectrum of techniques designed to enh...

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Semantic Scholar 118 Citations
Paper Information Summary
Entity Passport
Registry ID 001cca7910f507f7f75b8402b826c2dc07afef00
License ArXiv
Provider semantic_scholar
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Cite this paper

Academic & Research Attribution

BibTeX 
@misc{001cca7910f507f7f75b8402b826c2dc07afef00,
  title = {Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models Paper},
  howpublished = {\url{https://api.semanticscholar.org/001cca7910f507f7f75b8402b826c2dc07afef00}},
  note = {Accessed via Free2AITools.}
}
APA Style
Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models [Paper]. Free2AITools. https://api.semanticscholar.org/001cca7910f507f7f75b8402b826c2dc07afef00

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Full Specifications [+]

⚖️ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 87
Popularity (P) 64
Recency (R) 100
Quality (Q) 65

💬 Index Insight

FNI V2.0 for Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models: Authority (A:87), Popularity (P:64), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

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HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
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📝 Executive Summary

"The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated models like OpenAI’s ChatGPT, represents a significant advancement in artificial intelligence. These models, however, bring forth substantial challenges in high consumption of computational, memory, energy, and financial resources, especially in environments with limited resource capabilities. This survey aims to systematically address these challenges by reviewing a broad spectrum of techniques designed to enh..."

❝ Cite Node 

@article{Beyond,
  title={Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models},
  note={Indexed by Free2AITools}
}

🔗 Full Paper

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📊 Research Signals

📈118CitationsSemantic Scholar
🏛️87AuthorityFNI pillar
⏱️100RecencyFNI pillar
✅65QualityFNI pillar
🗂️text generationField

🏷️ Research Topics

chat models
📦Data Source: semantic_scholar
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Source summary: Based on semantic_scholar metadata. Not a recommendation.

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🆔 Identity & Source

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

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downloads
0
citations
118

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