Paper: Are Pathology Foundation Model Latent Representations Invariant to Rotation?
iScienceLuvr · x · 2026-08-25
This study investigates the rotational invariance of latent representations across 12 foundation models for digital pathology. By quantifying alignment between non-rotated and rotated patches, models trained with rotation augmentation showed significantly greater invariance. The findings suggest that the lack of rotational inductive bias in transformers necessitates such augmentation during training.
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