来源简介
arXiv:2606.00820v2 Announce Type: replace Abstract: Multi-agent debate (MAD) among large language models (LLMs) is often judged by answer changes and convergence, yet these outcomes alone cannot establish that peers improved the answer. We study this gap with matched self-reflection, stance-only, and full-reasoning conditions. With five GPT-4o agents on MMLU-Pro disagreement questions, 37% of agent-question pairs change even without peer information. Among pairs stable under this control, 29.3% adopt a peer answer after seeing peer stances. These adoptions include corrections, new errors, and changes between wrong answers. The outcomes vary with correct-answer availability. When a correct peer answer is available, correction exceeds harmful adoption after accounting for peer support in the primary setting. Full reasoning improves individual accuracy but provides no additional majority-vote gain over self-reflection while using 57% more tokens. Responses to constructed peer materials vary across GPT-4o, DeepSeek-V4-Flash, and Qwen3-Plus. An answer-agnostic intervention suppresses both harmful and beneficial peer adoption without a detectable accuracy gain. Together, the results show that convergence is an ambiguous signal of value and that debate must be judged by what peer information contributes to the final group answer.
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采集于 2026/10/20 21:06:31（北京时间）。 arXiv 日期为本次公告时间，论文初次投稿日期请查看原文版本记录。