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School of Cyber Science and Engineering, Qufu Normal University, Qufu, Shandong, China
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Truncating diffusion with motion primitives unlocks faster, more diverse mobile manipulator trajectories compared to vanilla diffusion and classical planners.
Transformer-based visual trackers, thought to be robust, can be significantly disrupted by patch-targeted adversarial noise, requiring far fewer queries than previously thought.
