MoEITS is an information-theoretic algorithm for pruning experts in MoE-LLMs that produces models with higher accuracy and greater size reduction than prior state-of-the-art methods on Mixtral 8x7B, Qwen1.5-2.7B, and DeepSeek-V2-Lite.
How good are low-bit quantized llama3 models? an empirical study.CoRR, abs/2404.14047
2 Pith papers cite this work. Polarity classification is still indexing.
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LLM-TALE steers RL exploration using LLM-generated plans at task and affordance levels with online suboptimality correction, improving sample efficiency and success rates on pick-and-place tasks without human supervision.
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MoEITS: A Green AI approach for simplifying MoE-LLMs
MoEITS is an information-theoretic algorithm for pruning experts in MoE-LLMs that produces models with higher accuracy and greater size reduction than prior state-of-the-art methods on Mixtral 8x7B, Qwen1.5-2.7B, and DeepSeek-V2-Lite.
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LLM-Guided Task- and Affordance-Level Exploration in Reinforcement Learning
LLM-TALE steers RL exploration using LLM-generated plans at task and affordance levels with online suboptimality correction, improving sample efficiency and success rates on pick-and-place tasks without human supervision.