AI RESEARCH
Aligning Cellular Sheaves with Classifier Attention for Interpretable Weakly-Supervised Pathology Localization
arXiv CS.AI
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ArXi:2606.00092v1 Announce Type: cross Weakly-supervised classification of whole-slide images with attention-based multiple instance learning (ABMIL) on top of foundation features now reaches near-saturation on Camelyon16 slide-level performance, but the corresponding attention maps are an imperfect localization signal: in clinical interpretation, a model that classifies correctly without firing on the actual lesion is hard to trust.