MedUAG: Unified Understanding and Generation for Medical Multimodal Models
This work develops MedUAG, an end-to-end trained unified medical model that achieves strong performance across a wide array of understanding and generation tasks, establishing a competitive baseline and paving the way for next-generation medical multimodal systems.
Zijie Meng, Yuncheng Zhang, Hualiang Wang et al.
· 0 citations