WM-DAgger: Enabling Efficient Data Aggregation for Imitation Learning with World Models
DGX agentarXiv:2604.11351v1 Announce Type: new Abstract: Imitation learning is a powerful paradigm for training robotic policies, yet its performance is limited by compounding errors: minor policy inaccuracies