AI RESEARCH

Easier to Mislead Than to Correct: Harmful and Beneficial Revision in LLM Conformity

arXiv CS.AI

ArXi:2606.01637v1 Announce Type: cross Large language models are increasingly used in multi-agent systems, where they see and respond to other agents' answers. A key risk is conformity: a model may abandon its own answer simply because others agree on a different one. Prior studies show that LLMs often revise toward a majority answer, but it remains unclear whether these revisions help correct mistakes as often as they