EVA: Aligning Video World Models with Executable Robot Actions via Inverse Dynamics Rewards
Video generative models are increasingly used as world models for robotics, where a model generates a future visual rollout conditioned on the current observation and task instruction, and an inverse dynamics model (IDM) converts the generated frames into executable robot actions. However, current video world models lack explicit executability constraints. As a result, visually coherent rollouts may still violate rigid-body and kinematic consistency, producing unstable or infeasible control commands when decoded by an IDM. We refer to this mismatch between visual generation and physically executable control as the executability gap. While this gap can be mitigated at inference time using ...
| Authors | Ruixiang Wang, Qingming Liu, Yueci Deng et al. |
|---|---|
| Primary category | cs.RO |
| Published | 18 March 2026 |
| Last updated at source | 24 March 2026 |
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