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Robots can now plan complex, long-horizon tasks in novel environments by predicting sparse visual sub-goals, achieving 70% success in zero-shot real-world experiments.
Multi-step flow-matching policies can achieve single-step control latencies by pipelining partially denoised action trajectories through an asynchronous rolling buffer.
Assistive robots no longer require invasive visual cameras to track human gestures, successfully executing closed-loop manipulation through physical privacy curtains via mmWave radar and state-space temporal modeling.
Pretraining loss actively misleads video data curation: broad data coverage systematically beats aggressive quality filtering across downstream benchmarks in both Wan 2.1 and V-JEPA 2.1.
