ClinKD offers a novel cross-modal knowledge distillation framework that significantly improves multimodal large language models' ability to interpret medical images and answer clinical questions.

• Addresses spatial localization errors and medical image misinterpretation through innovative knowledge distillation
• Integrates specialized clinical knowledge from medical experts to enhance image understanding
• Achieves state-of-the-art performance across multiple medical VQA benchmarks
• Creates more accurate and reliable medical AI systems for clinical decision support

This research represents a significant step toward clinically viable AI assistants that can reliably interpret medical imaging and support healthcare professionals in diagnostic workflows.

ClinKD: Cross-Modal Clinical Knowledge Distiller For Multi-Task Medical Images