arXiv cs.CV
· Papers
PathFLIP: Fine-grained Language-Image Pretraining for Versatile Computational Pathology
arXiv:2512.17621v2 Announce Type: replace Abstract: While Vision-Language Models (VLMs) have achieved notable progress in computational pathology (CPath), the gigapixel scale and spatial heterogeneity of Whole Slide Images (WSIs) continue to pose challenges for multimodal understanding. Existing alignment methods strug