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RoboEdit transforms abundant human manipulation videos into high-fidelity training data for robots, unlocking new avenues for scalable robot learning.
Temporal context boosts PCVR prediction accuracy significantly, revealing the critical importance of user behavior dynamics in recommender systems.
Finally, a feed-forward method can generate realistic, simulation-ready garment patterns directly from single "in-the-wild" images, bypassing the need for multi-view inputs or expensive optimization.
Origami, the "Hello, World!" of physical intelligence, is now tractable: Learn2Fold uses LLMs and graph-structured world models to generate valid folding sequences from text.
