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BIFOLD -Berlin Institute for the Foundations of Learning and Data, Technische Universität Berlin, Korea University, Max Planck Institute for Informatics
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Observed sample displacements can be integrated into optimal transport to carve expressways through the input space, leading to more reliable modeling of distribution shifts.
Human-inspired context sensitivity boosts visual reasoning in machines, closing the gap between AI and human perception.
Attention heatmaps in MIL models for histopathology are often misleading, and simpler methods like perturbation or LRP provide more faithful explanations.
