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Do Center Biases Propagate? Robustness of Pathology Foundation Models in Whole-Slide Image Classification

arXiv · AI, language, vision and robotics · article · Sep 23, 2026 · UTC

Pathology foundation models (PFMs) have transformed computational pathology through powerful representation learning from histopathological images. PFMs provide rich, discriminative representations for whole slide image (WSI) analysis, enabling tasks such as slide-level classification under multiple instance learning (MIL). However, these representations may also encode non-biological signals associated with acquisition centers, potentially introducing spurious shortcuts into downstream predictions. In this work, we evaluate center-associated robustness in WSI classification using a controlled

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