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Universal image editing models are surprisingly competitive with specialized virtual try-on systems, but still stumble when handling multiple garments simultaneously.
Diffusion models can learn surprisingly generalizable anatomical representations from unlabeled MRI data, enabling accurate multi-task diagnosis and segmentation across different joints and imaging conditions, even with limited labeled data.
