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A function-preserving Real-to-Sim-to-Real framework that generates synthetic demonstrations from reconstructed assets without teleoperated source trajectories is proposed, enabling robust generalization across unseen object geometries and diverse visual conditions in contact-rich and long-horizon tasks.
