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#artificial intelligence Preprint Sep 2026

Explainability from Training with Applications to TCR-Epitope Prediction

Deep learning models have achieved strong performance in artificial intelligence for science, yet their black-box nature limits our understanding of how they learn scientific tasks. Existing methods for interpretability provide limited insight into how models organize evidence and evolve during learning. We introduce e...

Jiarui Li, Zi-Xiang Yin, S. Landry et al. · 0 citations

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