AIoT-MLSys-Lab/Efficient-LLMs-Survey
[TMLR 2024] Efficient Large Language Models: A Survey
This survey paper helps researchers and practitioners navigate the rapidly evolving landscape of Large Language Models (LLMs) by offering a structured overview of techniques designed to improve their efficiency. It takes in existing research papers on LLM optimization and organizes them into a clear taxonomy, outputting a systematic understanding of different approaches. This resource is intended for AI researchers, machine learning engineers, and data scientists who are working with LLMs and need to make them more performant or cost-effective.
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Use this if you need a comprehensive, structured overview of techniques for making Large Language Models (LLMs) more efficient, covering model, data, and framework perspectives.
Not ideal if you are looking for an off-the-shelf tool or code implementation for LLM efficiency, as this is a survey and review of existing methods.
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