AI RESEARCH
Concepts in Motion: Temporal Concept Bottleneck Model for Interpretable Video Classification
arXiv CS.CV
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ArXi:2509.20899v3 Announce Type: replace Concept Bottleneck Models (CBMs) enable interpretable image classification by structuring predictions around human-understandable concepts, but extending this paradigm to video remains challenging due to the difficulty of extracting concepts and modeling them over time. In this paper, we