DVG-WM: Disentangled Video Generation Enables Efficient Embodied World Model for Robotic Manipulation

• URL: http://arxiv.org/abs/2606.32028v2
• Date: Thu, 02 Jul 2026 02:48:47 GMT
• Title: DVG-WM: Disentangled Video Generation Enables Efficient Embodied World Model for Robotic Manipulation
• Abstract summary: We present Disentangled Video Generation World Model (DVG-WM), an efficient framework that decomposes world modeling into dynamics learning and visual synthesis.<n> Experiments on LIBERO and real-world platforms demonstrate improved video quality with up to 3.97 times acceleration.
• Score: 41.032627534378065
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Video-based embodied world models provide an appealing substrate for robotic manipulation by predicting future states, yet current approaches remain limited by a fundamental entanglement: accurately modeling dynamics typically requires low-level temporal reasoning, while producing high-resolution frames demands expansive visual synthesis according to high-level semantics. This entanglement results in slow inference speed for iterative planning or too coarse predictions to retain contact-rich details. To solve this dilemma, we present Disentangled Video Generation World Model (DVG-WM), an efficient framework that explicitly decomposes world modeling into dynamics learning and visual synthesis. Conditioned on an initial observation and a language instruction, our model first generates a plausible sequence of intermediate visual states to preview the physical interaction and refines them to obtain high-fidelity videos. Furthermore, an efficient cascading mechanism is proposed, where DVG-WM uses flow matching to directly map the dynamics to video latents, and introduces a latent degradation mechanism to regenerate contact-rich details. Experiments on LIBERO and real-world platforms demonstrate improved video quality with up to 3.97 times acceleration, validating that disentangled video generation can be an efficient embodied world model for robotic manipulation.

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