Self-Refine Learning in LLM Multi-Agent Systems for Legal Norm Cognition and Compliance
A TBC-TBA self-refine learning multi-agent framework that enables dynamic normative adaptation through iterative multi-agent feedback that integrates Think-Before-Chat (social feedback processing) and Think-Before-Act (norm-guided decision making) phases, allowing agents to progressively refine their normative understanding via structured interaction cycles.
Rongxin Cheng, Jianhui Yang, Bo-Han Xiong et al.
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