AI RESEARCH
Architecture-Aware Explanation Auditing for Industrial Visual Inspection
arXiv CS.LG
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ArXi:2605.14255v1 Announce Type: new Industrial visual inspection systems increasingly rely on deep classifiers whose heatmap explanations may appear visually plausible while failing to identify the image regions that actually drive model decisions. This paper operationalizes an architecture-aware explanation audit protocol grounded in the native-readout hypothesis: the perturbation-based faithfulness of an explanation method is bounded by its structural distance from the model's native decision mechanism.