AIoT-MLSys-Lab/Efficient-LLMs-Survey resource

Health v2 · maintenance only

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Adoption not part of the score

1257 stars · 100 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A curated survey repository accompanying the TMLR 2024 paper 'Efficient Large Language Models: A Survey', organizing research on efficient LLMs into model-centric, data-centric, and framework-centric taxonomies. It is actively maintained with new papers added via pull requests.

Use cases

• find papers on efficient LLM inference and training
• learn about LLM efficiency techniques like quantization and pruning
• get an overview of efficient deep learning research for large language models
• find a taxonomy of model-centric and data-centric LLM efficiency methods
• keep up with new research on efficient large language models
• find citations for a literature review on LLM efficiency

When to choose

• you need a structured, peer-reviewed overview of efficient LLMs research
• you are starting research on LLM efficiency and want a reading list
• you want a maintained collection of papers on quantization, pruning, and efficient inference

When to avoid

• you need runnable software or tools rather than a paper collection
• you need production-ready efficiency implementations
• you need a license permitting redistribution, since no license is specified

Facets

learning-resource · maturity active

documentation developer-tools large-language-models machine-learning artificial-intelligence tutorials awesome-lists cross-platform survey-paper efficient-llms model-compression quantization efficient-inference efficient-training tmlr paper-collection

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markdown · JSON · MCP: product_card(name="AIoT-MLSys-Lab/Efficient-LLMs-Survey")