SOURCE-LINKED INTELLIGENCE
XPACE: Joint World and Action Modeling from Heterogeneous Experience
A general-purpose robot needs to draw on diverse experience, choose actions, and anticipate how those actions will change the world. We introduce XPACE, a unified embodied world model that serves as both a world action model, jointly predicting executable robot actions and future video, and a world simulator, predicting the visual consequences of prescribed actions. Our key insight is that video prediction can both connect heterogeneous experience to action learning and generate new experience for policy improvement. With a shared video backbone between the policy and simulator, we use action-
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T16:07:34.000Z
First collected: 2026-09-20T08:40:59.508Z. This is not the publication date.