Collaborative Reasoner - Self-Improving Social Agents with Synthetic Conversations
Collaborative Reasoner (Coral), a framework for evaluating and enhancing the collaborative reasoning skills of Language Models (LLMs) in multi-turn conversational settings, which are often overlooked in single-turn evaluations. Coral addresses the challenge of limited conversational data by proposing a self-improvement method that utilizes Matrix, a scalable multi-agent communication framework, to generate synthetic interaction data through simulated self-collaborations of LLMs.
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