CaliDist: Calibrating Large Language Models via Behavioral Robustness to Distraction 事件

CaliDist: Calibrating Large Language Models via Behavioral Robustness to Distraction arXiv:2606.05799v1 Announce Type: cross Abstract: Existing calibration methods for Large Language Models (LLMs) often overlook a critical dimension of trustworthiness: a model's {\em behavioral robustness} to irrelevant or misleading information. In this paper, we argue that a model's true confidence should reflect its stability under cognitive pressure. We introduce \textsc{CaliDist}, a novel post-hoc calibrat