用嘴玩3D世界：视频生成器正在变成游戏引擎
现在的AI视频生成器不只是生成视频，它正在变成你能实时操控的3D世界。研究者发现，当视频模型足够大时，语言本身就变成了控制手柄——你直接说“让角色向左走、镜头拉近”，它就能照做，不需要额外训练动作模块。他们在此基础上把这种粗粒度控制变成精确的时间轴控制：每条指令只作用于它该生效的那几秒，不会串味。整个系统只用了8000条游戏录像、改了0.199%的参数，就实现了角色和镜头的双控，还能泛化到没见过的场景。这不是你明天能玩到的产品，但它指向一个更近的未来：游戏不再需要写代码，你描述世界，世界就动起来。
📄 原文摘要(英文)
We present H3-World, an efficient framework that turns the 33B MiniMax-H3 video generator into an interactive world model. Our key finding is that, as large video generators become more capable, language is emerging as a natural interface for control. MiniMax-H3, for example, already supports zero-shot control of character behavior and camera motion through natural-language instructions. Building on this, H3-World turns this coarse language interface into precise, temporally grounded world control, without introducing dedicated action modules. Specifically, we represent each action as a structured combination of character and camera instructions, and align them with the corresponding temporal video latents. To make the control temporally precise, we further introduce temporal attention routing, which restricts each instruction to its intended time interval and reduces control leakage across actions. Importantly, H3-World directly reuses the semantic representations learned during large-scale video pretraining and requires only lightweight adaptation. With only 8,000 gameplay samples, 10,000 LoRA optimization steps, and 0.199% trainable parameters, H3-World achieves effective character and camera control while preserving strong generation quality. It also generalizes to unseen scenarios. These results show that the control capabilities emerging in large video generators can be efficiently transformed into interactive world control.