AI RESEARCH

Confidence Estimation for LLMs in Multi-turn Interactions

arXiv CS.CL

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.