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Achieving accurate trajectory predictions by recovering fine-grained details and capturing long-range dependencies could redefine how we model object dynamics in AI systems.
Agents trained with SEE-generated trajectories not only navigate complex multi-step procedures but also achieve unprecedented task success rates in real-world applications.
Image editing can boost multimodal LLM reasoning by 5 points, but only if the editor is trained to understand the reasoning process itself.
