AI RESEARCH
Confidence Estimation for LLMs in Multi-turn Interactions
arXiv CS.CL
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ArXi:2601.02179v2 Announce Type: replace While confidence estimation is a promising direction for mitigating hallucinations in Large Language Models (LLMs), current research overwhelmingly focuses on single-turn settings. The dynamics of model confidence in multi-turn conversations, where context accumulates and ambiguity is progressively resolved, remain largely unexplored.