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A counterfactual explanation is derived from a pair of discriminant explanations. Given a query image (Cardinal) and a counterfactual class (Summer Tanager), discriminant explanations are obtained by combining attribution maps for each of the two classes and the confidence score. In this way, they bridge the gap between attributive and counterfactual explanations, enabling fast optimization-free computation of the latter.

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