AI RESEARCH
ShapBPT: Image Feature Attributions Using Data-Aware Binary Partition Trees
arXiv CS.LG
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ArXi:2602.07047v3 Announce Type: replace-cross Pixel-level feature attributions are an important tool in eXplainable AI for Computer Vision (XCV), providing visual insights into how image features influence model predictions. The Owen formula for hierarchical Shapley values has been widely used to interpret machine learning (ML) models and their learned representations. However, existing hierarchical Shapley approaches do not exploit the multiscale structure of image data, leading to slow convergence and weak alignment with the actual morphological features.