This research provides a comprehensive evaluation framework for Large Vision-Language Models in medical contexts, particularly with radiological images.

• Introduces RadVUQA, a specialized benchmark for medical image analysis
• Evaluates models beyond simple visual question answering, including anatomical understanding
• Reveals significant gaps between current LVLM capabilities and real medical requirements
• Highlights the need for domain-specific training and evaluation metrics

This work matters because it cuts through the hype to provide realistic expectations of AI models in healthcare, identifying both opportunities and limitations for clinical applications.

Beyond the Hype: A dispassionate look at vision-language models in medical scenario