3 papers
cs.AI2026
RadAgent: A tool-using AI agent for stepwise interpretation of chest computed tomography
Mélanie Roschewitz, Kenneth Styppa, Yitian Tao +10
Vision-language models (VLM) have markedly advanced AI-driven interpretation and reporting of complex medical imaging, such as computed tomography (CT). Yet, existing methods large…
cs.CV2026
Universal Boosts, Specific Suppressors: Sparse Autoencoder Steering of Medical Vision-Language Models
Farhad Nooralahzadeh, Benjamin Gundersen, Nicolas Deperrois +7
Medical vision-language models (VLMs) often hallucinate findings when generating chest X-ray reports: they fabricate findings that are not present in the image, miss important ones…
cs.AI2025
Enhancing Radiology Report Generation and Visual Grounding using Reinforcement Learning
Benjamin Gundersen, Nicolas Deperrois, Samuel Ruiperez-Campillo +5
Recent advances in vision-language models (VLMs) have improved Chest X-ray (CXR) interpretation in multiple aspects. However, many medical VLMs rely solely on supervised fine-tunin…