X-World 1.6 发布：用世界模型构建可控虚拟城市
X-World 1.6: Building Controllable Virtual Cities with World Models
X-World 1.6 把世界模型做成了自动驾驶仿真器，能从一张图生成多摄像头视频，还能精细控制红绿灯和车道线，做闭环测试的可以看看。
X-World 1.6 在 X-World 1.0 基础上升级为更可靠的自动驾驶仿真器。新基础模型支持对红绿灯、道路标线等交通语义的细粒度控制，并提升多摄像头间的空间一致性。Virtual City 能力可基于 2D 和 3D 参考生成场景，包括从单张图像生成多摄像头未来视频。后训练框架支持因果式少步生成，在更长 rollout 中保持时间连贯性与画面质量，并附带一套专用评测套件。
X-World 1.6: Building Controllable Virtual Cities with World Models
Deploying generative world models for end-to-end closed-loop evaluation and policy learning requires precise scenario control, consistent observations, and sustained generation quality during extended interactions. This report presents \emph{X-World~1.6}, advancing X-World~1.0 toward a more reliable and versatile driving simulator. The upgraded base model offers finer-grained control over traffic semantics, including traffic lights and road markings, together with improved spatial consistency across cameras. Virtual City capabilities broaden scenario construction through a family of models conditioned on diverse 2D and 3D references, including support for generating multi-camera future videos from a single image. An enhanced post-training framework enables efficient causal, few-step generation with stronger temporal coherence, better quality retention over longer rollouts, and improved alignment with human preferences. We also introduce a dedicated evaluation suite to support systematic assessment and guide model iteration. Together, these upgrades expand the scenarios X-World can simulate and improve the efficiency and reliability of its generated observations, supporting broader use in autonomous-driving development.
