vMFProto models each class as a mixture of von Mises-Fisher components on the hypersphere, learns per-prototype concentrations, and applies entropic OT for assignments, yielding SOTA explanation quality on CUB, Dogs, and Cars with frozen DINO backbones.
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Beyond Points: Spherical Distributional Part Prototypes for Interpretable Classification
vMFProto models each class as a mixture of von Mises-Fisher components on the hypersphere, learns per-prototype concentrations, and applies entropic OT for assignments, yielding SOTA explanation quality on CUB, Dogs, and Cars with frozen DINO backbones.