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Even state-of-the-art MLLMs fail to grasp intuitive visual reasoning, scoring less than 60% on tasks humans solve effortlessly at a glance.
A groundbreaking dataset and benchmark that bridges the gap between anatomical and metabolic analysis in whole-body PET/CT imaging, enabling advanced multimodal reasoning.
A unified Vision-Language Model and Diffusion architecture unlocks surprisingly effective optical flow forecasting from noisy web data, enabling language-conditioned robot control and video generation.