X-Cache: Cross-Chunk Block Caching for Few-Step Autoregressive World Models Inference
Real-time world simulation is becoming a key infrastructure for scalable evaluation and online reinforcement learning of autonomous driving systems. Recent driving world models built on autoregressive video diffusion achieve high-fidelity, controllable multi-camera generation, but their inference cost remains a bottleneck for interactive deployment. However, existing diffusion caching methods are designed for offline video generation with multiple denoising steps, and do not transfer to this scenario. Few-step distilled models have no inter-step redundancy left for these methods to reuse, and sequence-level parallelization techniques require future conditioning that closed-loop interactiv...
| Authors | Yixiao Zeng, Jianlei Zheng, Chaoda Zheng et al. |
|---|---|
| Primary category | cs.CV |
| Published | 22 April 2026 |
| Last updated at source | 5 May 2026 |
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