AI RESEARCH
SetFlow: Generating Structured Sets of Representations for Multiple Instance Learning
arXiv CS.LG
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ArXi:2604.16362v1 Announce Type: new Data scarcity and weak supervision continue to limit the performance of machine learning models in many real-world applications, such as mammography, where Multiple Instance Learning (MIL) often offers the best formulation. While recent foundation models provide strong semantic representations out of the box, effective augmentation of such representations of MIL data remains limited, as existing methods operate at the instance level and fail to capture intra-bag dependencies. In this work, we.