AI世界模型终于记得住自己刚带你看过哪了
现在的AI世界模型有个结构性毛病：它要听你指挥，就得只盯着眼前几帧；它要记住带你看过的地方，又得记住全部历史。这两件事在架构上互相打架，所以大多数模型玩着玩着就忘了自己刚给你看过什么。ReWorld把这两件事拆开：大部分注意力窗口只管最近几帧，少数几个全局窗口负责翻旧账，推理时再用一个按位置索引的地标库兜底——你走远了，它还能从库里把离你最近的场景捞回来。在64秒的长路线测试里，别的模型早把起点忘光了，它还能原样重现你出发时那个画面。这不是你明天能玩上的东西，但它指向一个关键拐点：世界模型从“能生成画面”走向“能陪你逛完一个地方还不迷路”。
📄 原文摘要(英文)
An interactive world model must follow the user's actions, remember the places it has shown, and stream in real time. The tension is structural: control wants a short horizon, memory wants an unbounded one. ReWorld separates the two during training and bounds them at inference. Mixed per-head attention windows confine most heads to the recent past while a small set of global heads attends over the entire history, and random head routing keeps either capability from binding to particular heads; random chunk dropping makes sparse histories in-distribution. At inference the whole past lives under a fixed budget: a bounded KV cache backed by a pose-indexed landmark bank, from which the model retrieves the landmarks nearest the current pose. A metric-scale-aligned data engine places eight sources -- Unreal-rendered fly-throughs, game roaming, and real-world footage -- on one physical action scale, so the same key press moves the camera the same distance in every source, and palindrome trajectories supply the revisit evidence that memory training needs. Distribution-matching distillation confined to a LoRA adapter then compresses sampling to four steps: one backbone serves both a high-fidelity multi-step mode and a real-time interactive one, streaming 704x1280 video across photorealistic, game-style, and stylized worlds. Under a three-axis protocol covering action following, long-horizon recall, and video quality, against six recent interactive world models it attains the best control fidelity (11.95^circ rotation error and the best camera-motion consistency) and the best generation quality; and on minute-long out-and-back rollouts (64\,s, 384 latents), its fixed 12-chunk cache still regenerates the starting view -- at rollout lengths where a sliding window has long evicted the evidence and full-KV attention runs out of memory.