HelloWorld: Towards Practical Applications of Generative Driving World Models
Driving world models provide a promising route toward scalable counterfactual data generation and interactive simulation beyond recorded driving logs. Realizing this potential requires a system that can generalize across diverse scenes, respond faithfully to prescribed controls, generate coherent multi-sensor observations, and operate efficiently under repeated inference. We present \textbf{HelloWorld}, a 2B driving world model system designed around these requirements. HelloWorld progressively specializes broad visual and motion priors from heterogeneous video data into controllable driving generation using ego pose, HD maps, and 3D boxes. A block-causal generation interface, together wi...
| Authors | Fan Lu, Hanshi Wang, Zijing Wang et al. |
|---|---|
| Primary category | cs.CV |
| Published | 24 September 2026 |
| Last updated at source | 24 September 2026 |
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