LLMs Uncertainty Quantification via Adaptive Conformal Semantic Entropy 事件

LLMs Uncertainty Quantification via Adaptive Conformal Semantic Entropy arXiv:2605.04295v2 Announce Type: replace-cross Abstract: LLMs' overconfidence, particularly when hallucinating, poses a significant challenge for the deployment of the models in safety-critical settings and makes a reliable estimation of uncertainty necessary. Existing approaches for uncertainty quantification typically prioritize lexical or probabilistic measures; however, these techniques often ignore the semantic varian