Calibration vs Decision Making: Revisiting the Reliability Paradox in Unlearned Language Models

Machine unlearning aims to remove the influence of specific training data from a model while preserving reliable behavior on the remaining data, making reliable prediction and uncertainty estimation essential for evaluation. Calibration is commonly used as a proxy for reliability in language models,...