Scalable and reliable evaluation is increasingly critical in the end-to-end era of autonomous driving, where vision--language--action (VLA) policies directly map raw sensor streams to driving actions. Yet, current evaluation pipelines still rely heavily on real-world road testing, which is costly, biased toward limited scenario coverage, and difficult to reproduce. These challenges motivate a real-world simulator that can generate realistic future observations under proposed actions, while remaining controllable and stable over long horizons. We present X-World, an action-conditioned multi-camera generative world model that simulates future observations directly in video space. Given synchronized multi-view camera history and a future action sequence, X-World generates future multi-camera video streams that follow the commanded actions. To ensure reproducible and editable scene rollouts, X-World further supports optional controls over dynamic traffic agents and static road elements, and retains a text-prompt interface for appearance-level control (e.g., weather and time of day). Beyond world simulation, X-World also enables video style transfer by conditioning on appearance prompts while preserving the underlying action and scene dynamics. At the core of X-World is a multi-view latent video generator designed to explicitly encourage cross-view geometric consistency and temporal coherence under diverse control signals. Experiments show that X-World achieves high-quality multi-view video generation with (i) strong view consistency across cameras, (ii) stable temporal dynamics over long rollouts, and (iii) high controllability with strict action following and faithful adherence to optional scene controls. These properties make X-World a practical foundation for scalable and reproducible evaluation.

翻译：在端到端自动驾驶时代，可扩展且可靠的评估愈发关键。该时代下，视觉-语言-动作（VLA）策略直接将原始传感器数据流映射为驾驶行为。然而，当前评估管线仍严重依赖真实道路测试，其成本高昂、场景覆盖范围有限且难以复现。这些挑战促使我们构建一种真实世界模拟器：能够在给定拟定动作下生成逼真的未来观测结果，同时保持长时域内的可控性和稳定性。我们提出X-World——一种基于动作条件的多摄像头生成式世界模型，可直接在视频空间模拟未来观测。给定同步多视角摄像头历史数据及未来动作序列，X-World可生成遵循指令动作的未来多摄像头视频流。为确保场景推演的可复现性与可编辑性，X-World进一步支持对动态交通智能体和静态道路元素的可选控制，并保留用于外观级控制（如天气和时段）的文本提示接口。除世界模拟外，X-World还支持视频风格迁移——通过外观提示进行条件控制，同时保留底层动作与场景动态。X-World核心是一个多视角潜变量视频生成器，其设计旨在显式增强跨视角几何一致性与时间连贯性，并兼容多样化控制信号。实验表明，X-World能生成高质量多视角视频，具备：(i) 摄像头间强视角一致性，(ii) 长推演过程中的稳定时间动态，(iii) 高可控性——严格遵循动作指令并忠实执行可选场景控制。这些特性使X-World成为可扩展、可复现评估的实用基础。