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Found 2 papers, 1 papers with code
Robust Semantic Interpretability: Revisiting Concept Activation Vectors
Our proposed Robust Concept Activation Vectors (RCAV) quantifies the effects of semantic concepts on individual model predictions and on model behavior as a whole.
Global Saliency: Aggregating Saliency Maps to Assess Dataset Artefact Bias
In high-stakes applications of machine learning models, interpretability methods provide guarantees that models are right for the right reasons.
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