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Robots can now achieve over double the success rate in using novel tools by leveraging keypoint trajectory reasoning for functional generalization.
Causal Spectral Policy achieves superior performance in precision-sensitive tasks by effectively separating motion intent from execution details, revealing a new paradigm in hierarchical policy learning.
DEHP dramatically boosts the success rates of high-precision robotic tasks by dynamically adjusting execution horizons based on task complexity.
Achieve minute-level navigable video world models by combining the strengths of explicit 3D patch memory with implicit generative modeling.
