Author

G. Angulo

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Preprint Aug 2026

OPAL: Orthonormal Prototype Alignment Learning for Interpretable Image Classification

This work introduces Orthonormal Prototype Alignment Learning (OPAL), a single-stage, end-to-end framework that simplifies interpretable classification by framing classification as a direct representation alignment task, and eliminates the need for auxiliary losses.

I. Carretero, G. Angulo, R. del Amor et al. · 0 citations