Donglin Wang

Decoupling motion retargeting into a privileged generator and an anticipatory executor enables physical humanoids to mirror agile, expressive human motions in real time despite severe latency and embodiment mismatches.

RynnValue shows that using temporal distance as a supervision target can outperform traditional preference-based methods in robotic learning, achieving higher accuracy and broader generalization.