Introducing CARE-X: Towards Clinically Useful Radiology VLMs with Auxiliary Supervision, Reward-Aligned Learning, and Tool-Augmented Measurement
Microsoft Research released CARE-X, a unified chest X-ray vision-language research model for report generation and structured prediction. It rewards clinical correctness using multitask reinforcement learning (DAPO). Generation and dual-inference modes cover lesion presence and negation, localisation, multilabel classification, catheter and tube malposition detection, and localisation of 29 anatomical regions.