A Mechanistic Analysis of Sim-and-Real Co-Training in Generative Robot Policies

arXiv:2604.13645v1 Announce Type: cross Abstract: Co-training, which combines limited in-domain real-world data with abundant surrogate data such as simulation or cross-embodiment robot data, is widely used for training generative robot policies. Despite its empirical success, the mechanisms that...