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Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?

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arxiv 2402.18272 v1 pith:7DACMQI2 submitted 2024-02-28 cs.CL cs.AI

Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?

classification cs.CL cs.AI
keywords discussionllmsmulti-agentreasoningmechanismsabilitiesachieveagent
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Recent progress in LLMs discussion suggests that multi-agent discussion improves the reasoning abilities of LLMs. In this work, we reevaluate this claim through systematic experiments, where we propose a novel group discussion framework to enrich the set of discussion mechanisms. Interestingly, our results show that a single-agent LLM with strong prompts can achieve almost the same performance as the best existing discussion approach on a wide range of reasoning tasks and backbone LLMs. We observe that the multi-agent discussion performs better than a single agent only when there is no demonstration in the prompt. Further study reveals the common interaction mechanisms of LLMs during the discussion.

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