collaborators

21 papers

cs.CV2026

From Patches to Patients: A study of the tile-to-slide performance transferability in Digital Pathology

Sofiène Boutaj, Leo Fillioux, Maria Vakalopoulou +2

Foundation Models (FMs) have recently redefined the state-of-the-art in histopathology by providing robust representations for whole-slide image (WSI) analysis. However, selecting…

cs.CV2026

Medical Context Distorts Decisions in Clinical Vision Language Models

David Restrepo, Ira Ktena, Maria Vakalopoulou +2

Vision-language models (VLMs) are increasingly proposed for clinical decision support, yet their reliability in real-world scenarios that require integrating both visual and textua…

cs.CV2026

PVeRA: Probabilistic Vector-Based Random Matrix Adaptation

Leo Fillioux, Enzo Ferrante, Paul-Henry Cournède +2

Large foundation models have emerged in the last years and are pushing performance boundaries for a variety of tasks. Training or even finetuning such models demands vast datasets…

cs.LG2026

On the Cone Effect and Modality Gap in Medical Vision-Language Embeddings

David Restrepo, Miguel L Martins, Chenwei Wu +5

Vision-Language Models (VLMs) exhibit a characteristic "cone effect" in which nonlinear encoders map embeddings into highly concentrated regions of the representation space, contri…

cs.CV2026

Information Maximization for Long-Tailed Semi-Supervised Domain Generalization

Leo Fillioux, Omprakash Chakraborty, Quentin Gopée +6

Semi-supervised domain generalization (SSDG) has recently emerged as an appealing alternative to tackle domain generalization when labeled data is scarce but unlabeled samples acro…

cs.CV2026

Mask-HybridGNet: Graph-based segmentation with emergent anatomical correspondence from pixel-level supervision

Nicolás Gaggion, Maria J. Ledesma-Carbayo, Stergios Christodoulidis +2

Graph-based medical image segmentation represents anatomical structures using boundary graphs, providing fixed-topology landmarks and inherent population-level correspondences. How…