AI RESEARCH
MoEMambaMIL: Structure-Aware Selective State Space Modeling for Whole-Slide Image Analysis
arXiv CS.CV
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ArXi:2603.06378v1 Announce Type: new Whole-slide image (WSI) analysis is challenging due to the gigapixel scale of slides and their inherent hierarchical multi-resolution structure. Existing multiple instance learning (MIL) approaches often model WSIs as unordered collections of patches, which limits their ability to capture structured dependencies between global tissue organization and local cellular patterns. Although recent State Space Models (SSMs) enable efficient modeling of long sequences, how to structure WSI tokens to fully exploit their spatial hierarchy remains an open problem.