Shypd.aiThe largest open index of AI toolsEfficient-LLMs-Survey is an academic research survey that provides a comprehensive review of efficient large language models. It organizes literature into model-centric, data-centric, and framework-centric categories.
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Efficient-LLMs-Survey is a comprehensive academic survey focusing on efficient large language models (LLMs), published in Transactions on Machine Learning Research (TMLR) in May 2024. This resource systematically reviews techniques and methods for improving LLM efficiency, addressing the substantial resource demands of these powerful models. The survey categorizes the literature into three main areas: model-centric methods (e.g., compression, quantization, pruning), data-centric methods (e.g., data selection, prompt engineering), and framework-centric perspectives (e.g., system-level optimization, LLM frameworks). It serves as a valuable resource for researchers and practitioners seeking to understand the current landscape of efficient LLM research and inspire future contributions to the field.
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