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cs.CV2026
DALPHIN: Benchmarking Digital Pathology AI Copilots Against Pathologists on an Open Multicentric Dataset
Carlijn Lems, Sander Moonemans, Natálie Klubíčková +53
Foundation models with visual question answering capabilities for digital pathology are emerging. Such unprecedented technology requires independent benchmarking to assess its pote…
cs.CV2026
Designing UNICORN: a Unified Benchmark for Imaging in Computational Pathology, Radiology, and Natural Language
Michelle Stegeman, Lena Philipp, Fennie van der Graaf +20
Foundation models are changing the way we develop medical artificial intelligence. By learning broadly generalizable features across diverse data modalities, a single model can be…