【第186期】CoAT：MCTS+memory增强推理的框架
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CoAT: Chain-of-Associated-Thoughts Framework for Enhancing Large Language Models Reasoning
Summary
The provided research paper introduces CoAT, a novel framework designed to enhance the reasoning capabilities of large language models (LLMs). Inspired by human cognition, CoAT integrates Monte Carlo Tree Search (MCTS) for structured exploration of reasoning paths with an associative memory mechanism that dynamically incorporates new information. This synergy allows LLMs to revisit prior…
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