AI RESEARCH

Benchmarking Pathology Foundation Models for Spatial Domain Understanding

arXiv CS.AI

ArXi:2605.25764v1 Announce Type: cross Pathology foundation models (PFMs) have emerged as a core approach for learning transferable representations from whole slide images (WSIs), and they are typically benchmarked through downstream clinical endpoints. While such task level evaluations are indispensable, they offer limited insight into what the representations themselves encode, particularly whether PFM embeddings can distinguish meaningful tissue regions and capture their spatial relationships.