A distance-based softmax loss trained with scaled logits, unscaled at inference, plus an entropy score, improves out-of-distribution detection without extra data, tuning, or accuracy loss.
Distance- based image classification: Generalizing to new classes at near-zero cost,
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Entropic Out-of-Distribution Detection
A distance-based softmax loss trained with scaled logits, unscaled at inference, plus an entropy score, improves out-of-distribution detection without extra data, tuning, or accuracy loss.