most citedTowards Resource Efficient and Interpretable Bias Mitigation in Large Language Models

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cs.LG2026

Learning Concept Bottleneck Models from Mechanistic Explanations

Antonio De Santis, Schrasing Tong, Marco Brambilla +1

Concept Bottleneck Models (CBMs) aim for ante-hoc interpretability by learning a bottleneck layer that predicts interpretable concepts before the decision. State-of-the-art approac…