MIL-PF: Multiple Instance Learning on Precomputed Features for Mammography Classification

ArXi:2603.09374v1 Announce Type: cross Modern foundation models provide highly expressive visual representations, yet adapting them to high-resolution medical imaging remains challenging due to limited annotations and weak supervision. Mammography, in particular, is characterized by large images, variable multi-view studies and predominantly breast-level labels, making end-to-end fine-tuning computationally expensive and often impractical.