Aligning Cellular Sheaves with Classifier Attention for Interpretable Weakly-Supervised Pathology Localization 事件

Aligning Cellular Sheaves with Classifier Attention for Interpretable Weakly-Supervised Pathology Localization arXiv:2606.00092v1 Announce Type: new Abstract: 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 corre