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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…
cs.CV2020★ 8 cited
Investigating Bias in Image Classification using Model Explanations
Schrasing Tong, Lalana Kagal
We evaluated whether model explanations could efficiently detect bias in image classification by highlighting discriminating features, thereby removing the reliance on sensitive at…