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Eliana Pastor

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#artificial intelligence Preprint Oct 2026

Auditing Where Concept Bottleneck Accuracy Comes From on CUB

Concept Bottleneck Models (CBMs) promise predictions that humans can inspect and correct through concepts such as"curved beak". Yet on CUB-200-2011, their standard benchmark, progress is measured like that of ordinary classifiers: by task and concept accuracy. Neither reveals whether the label is predicted from the exp...

S. Saralajew, Eleonora Poeta, Eliana Pastor et al. · 0 citations
#artificial intelligence Open access Mar 2026

The MAMA-MIA Challenge: Advancing Generalizability and Fairness in Breast MRI Tumor Segmentation and Treatment Response Prediction

The MAMA-MIA Challenge provides standardized datasets, evaluation protocols, and public resources to promote the development of robust and equitable artificial intelligence systems for breast cancer imaging.

Lidia Garrucho, Smriti Joshi, Kaisar Kushibar et al. · 2 citations

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