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Sim-and-Human Co-training for Data-Efficient and Scene-Generalizable Bimanual Manipulation
Real-robot demonstrations are prohibitively expensive, while simulation data and real-world human demonstrations are both scalable but each leaves a distinct gap: simulation suffers from a sim-to-real visual gap, and human data suffers from a human-to-robot embodiment gap. In this work, we identify
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