Learning Concept Bottleneck Models from Mechanistic Explanations
Learning Concept Bottleneck Models from Mechanistic Explanations explores M-CBM extracts and names concepts learned by black-box models to build interpretable concept bottleneck models, improving performance and explainability.. Commercial viability score: 7/10 in Explainable AI.
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