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ODEWorld: A Continuous Predictive Architecture via Physical-Time Flow

7 upvotes · 30 JUL 2026 · Dongxiu Liu, Haoyi Niu, Peng Cheng et al.

This paper introduces ODEWorld, a new approach to modeling the physical world by learning a continuous latent velocity field that operates in physical time, allowing for more efficient and realistic predictions of future events. Practitioners in robotics and computer vision may care about ODEWorld's ability to provide rich planning-oriented information and high-quality image reconstruction.

physical-time flowcontinual learninglatent world modelsimage reconstructiontemporal integrationordinary differential equations (ODEs)