The Lighthouse of Language: Enhancing LLMAgents via Critique-Guided Improvement

Neural Information Processing Systems 

Large language models (LLMs) have recently transformed from text-based assistants to autonomous agents capable of planning, reasoning, and iteratively improving their actions. While numerical reward signals and verifiers can effectively rank candidate actions, they often provide limited contextual guidance.

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