Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?
<|reference_start|>Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?: 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.<|reference_end|>
@article{wang2024rethinking,
    title={Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the
  Key?},
    author={Qineng Wang, Zihao Wang, Ying Su, Hanghang Tong, Yangqiu Song},
    journal={arXiv preprint arXiv:2402.18272},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.18272},
    primaryClass={cs.CL cs.AI}
}