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Found 2 papers, 2 papers with code
The SaTML '24 CNN Interpretability Competition: New Innovations for Concept-Level Interpretability
Interpretability techniques are valuable for helping humans understand and oversee AI systems.
Prototype Generation: Robust Feature Visualisation for Data Independent Interpretability
We introduce Prototype Generation, a stricter and more robust form of feature visualisation for model-agnostic, data-independent interpretability of image classification models.
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