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

• URL: http://arxiv.org/abs/2402.18272v1
• Date: Wed, 28 Feb 2024 12:04:05 GMT
• Title: Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?
• Authors: Qineng Wang, Zihao Wang, Ying Su, Hanghang Tong, Yangqiu Song
• Abstract summary: We propose a novel group discussion framework to enrich the set of discussion mechanisms. We observe that the multi-agent discussion performs better than a single agent only when there is no demonstration in the prompt.
• Score: 84.36332588191623
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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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