MedGround: Bridging the Evidence Gap in Medical Vision-Language Models with Verified Grounding Data

Vision-Language Models (VLMs) can generate convincing clinical narratives, yet frequently struggle to visually ground their statements. We posit that this limitation arises from the scarcity of high-quality, large-scale clinical referring-localization pairs. To address this, we introduce MedGround,