Detecting Explanatory Insufficiency in Learned Representations: A Framework for Representational Vigilance

Learned representations are commonly evaluated through predictive performance, calibration, robustness, uncertainty estimation, and behavior under distribution shift. Yet these criteria do not determine whether the representation itself remains sufficient for organizing observations relevant to an e