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Karlsruhe Institute of Technology, Robotics Institute Germany
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SPARC reduces noisy labels by leveraging task structure, enabling robots to learn from more reliable demonstrations and outperforming traditional methods in real-world applications.
Current dual-arm manipulation policies falter in real-world applications, with significant challenges in early interactions and skill transfer from simulation.
Decoupling modality processing in VLA models leads to a staggering 95.2% success rate in complex manipulation tasks, far surpassing traditional synchronous approaches.
