World Action Learning via Interaction-Centric Spectral Latent Guidance

WING transfers task semantics from egocentric videos to robot policies by decoupling ego-camera motion from hand-object interactions. The framework uses spectral latent guidance to isolate interaction-centric signals, mitigating nuisance variations in latent action inference and addressing temporal dynamics mismatches between human and robotic behaviors.