Shu-Ze Wang

Mitigating Covariate Shift in Offline Imitation Learning via Trajectory Synthesis

Offline imitation learning (IL) is a practical route to embodied policy learning when online exploration is unsafe, expensive, or unavailable. Its main limitation is the closed-loop covariate shift: a policy trained only on fixed demonstrations can enter states outside the expert support, where behavioral cloning provi...