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cs.LG2026
Harmful Partial Interventions and Benign Leakage in Concept-based Models
Gregory Verghese, Christopher J. Soelistyo, Mateo Espinosa Zarlenga +2
Artificial intelligence systems deployed in high-risk settings increasingly require models that support meaningful human oversight. Concept-based models (CMs) offer a promising fra…
cs.LG2026
Concept frustration: Aligning human concepts and machine representations
Enrico Parisini, Christopher J. Soelistyo, Ahab Isaac +2
Aligning human-interpretable concepts with the internal representations learned by modern machine learning systems remains a central challenge for interpretable AI. We introduce a…