StaRFM reuses the authors' earlier CalShift penalties, extends them to 3D medical segmentation with patch-wise and voxel-wise variants, and claims large gains that are not consistently supported by the paper's own tables.
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Calibrated and Robust Foundation Models for Vision-Language and Medical Image Tasks Under Distribution Shift
StaRFM reuses the authors' earlier CalShift penalties, extends them to 3D medical segmentation with patch-wise and voxel-wise variants, and claims large gains that are not consistently supported by the paper's own tables.