World In-Context Learning for Agentic Robot Manipulation

World In-Context Learning (WICL) enables a frozen model to learn manipulation tasks through simulation rehearsal and deploy frozen Task Memory on new scenes with data isolation, as implemented in the RoboScript infrastructure.