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arXiv · 2310.15368

Deep Integrated Explanations

Oren Barkan·Yehonatan Elisha·Jonathan Weill·Yuval Asher·Amit Eshel·Noam Koenigstein
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Abstract

This paper presents Deep Integrated Explanations (DIX) - a universal method for explaining vision models. DIX generates explanation maps by integrating information from the intermediate representations of the model, coupled with their corresponding gradients. Through an extensive array of both objective and subjective evaluations spanning diverse tasks, datasets, and model configurations, we showcase the efficacy of DIX in generating faithful and accurate explanation maps, while surpassing current state-of-the-art methods.

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Oren Barkan, Yehonatan Elisha, Jonathan Weill, Yuval Asher, Amit Eshel, Noam Koenigstein. 2023-10-28. Deep Integrated Explanations. https://arxiv.org/abs/2310.15368

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