When Helping Hurts and How to Fix It: Multi-Agent Debate for Data Cleaning 事件

When Helping Hurts and How to Fix It: Multi-Agent Debate for Data Cleaning arXiv:2606.02866v1 Announce Type: cross Abstract: When does multi-agent debate help data cleaning, and when does it hurt? Across three benchmarks, four model families, and over 6,000 task-condition pairs, we find debate's effect reverses sign: it degrades generation across all four models (-1.6 to -15.5pp) through critique-induced confusion (CIC), hallucinated Critic feedback that the Generator accepts uncritically, yet