데브허브 | DEVHUB | "Slow Thinking LLMs" - Great idea in a poor paper!
Chain-of-Associated-Thoughts (CoAT) framework, which introduces an innovative synergy between the Monte Carlo Tree Search (MCTS) algorithm and a dynamic mechanism for integrating new key information, termed ‘associative memory’. By combining the structured exploration capabilities of MCTS with the adaptive learning capacity of associative memory, CoAT significantly expands the LLM search space, enabling our framework to explore diverse reasoning pathways and dynamically update its knowledge base in real-time.
CoAT: Chain-of-Associated-Thoughts Framework for Enhancing Large Language Models Reasoning
https://arxiv.org/pdf/2502.02390
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