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

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cs.CV2026

Mitigating Bias in Concept Bottleneck Models for Fair and Interpretable Image Classification

Schrasing Tong, Antoine Salaun, Vincent Yuan +2

Ensuring fairness in image classification prevents models from perpetuating and amplifying bias. Concept bottleneck models (CBMs) map images to high-level, human-interpretable conc…