Lost or Hidden? A Concept-Level Forgetting in Supervised Continual Learning

ArXi:2605.16374v1 Announce Type: new Continual learning studies how models can adapt to new tasks while retaining previously acquired knowledge. Although a broad spectrum of methods has been proposed to mitigate catastrophic forgetting, the field remains predominantly performance-driven, with limited insight into what forgetting actually corresponds to within the vision model's representation space.