Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models
Large-scale video generation models are increasingly described as world models because they can learn rich spatiotemporal regularities from visual data. However, we argue that an ideal world model should benefit in a self-evolving generative character. Traditional visually plausible predictions alone are not enough to establish whether an imagined future is physically actionable for a particular embodied agent, failing to provide informative feedback from environments for self-evolving improvement. To realize self-evolving world models, this article proposes the concept of autonomous video generation, which is evaluated through counterfactual controllability, i.e., the ability to i) gener...
| Authors | Xin Wang, Wenxuan Liu, Tongtong Feng et al. |
|---|---|
| Primary category | cs.CV |
| Published | 23 June 2026 |
| Last updated at source | 14 July 2026 |
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