5 papers · 1 filter
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…
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…
On the Risk of Misleading Reports: Diagnosing Textual Biases in Multimodal Clinical AI
David Restrepo, Ira Ktena, Maria Vakalopoulou +2
Clinical decision-making relies on the integrated analysis of medical images and the associated clinical reports. While Vision-Language Models (VLMs) can offer a unified framework…
Fairness and Robustness of CLIP-Based Models for Chest X-rays
Théo Sourget, David Restrepo, Céline Hudelot +3
Motivated by the strong performance of CLIP-based models in natural image-text domains, recent efforts have adapted these architectures to medical tasks, particularly in radiology,…
ViG-Bias: Visually Grounded Bias Discovery and Mitigation
Badr-Eddine Marani, Mohamed Hanini, Nihitha Malayarukil +3
The proliferation of machine learning models in critical decision making processes has underscored the need for bias discovery and mitigation strategies. Identifying the reasons be…