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AGOP as Explanation: From Feature Learning to Per-Sample Attribution in Image Classifiers

arXiv cs.LG ↗ · 2026-05-14 Cached

The paper introduces AGOP-Weighted, a post-hoc attribution method that multiplies per-sample gradients by a training-distribution prior to suppress noise and highlight important pixels, and demonstrates significant improvements over existing methods on synthetic and photorealistic benchmarks.

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