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cs.CV2025
Tell me why: Visual foundation models as self-explainable classifiers
Hugues Turbé, Mina Bjelogrlic, Gianmarco Mengaldo +1
Visual foundation models (VFMs) have become increasingly popular due to their state-of-the-art performance. However, interpretability remains crucial for critical applications. In…
cs.CV2024
ProtoS-ViT: Visual foundation models for sparse self-explainable classifications
Hugues Turbé, Mina Bjelogrlic, Gianmarco Mengaldo +1
Prototypical networks aim to build intrinsically explainable models based on the linear summation of concepts. Concepts are coherent entities that we, as humans, can recognize and…