# Code World Model：编码智能体作为世界大脑

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-08-26 08:00
- AIHOT 分数：52
- AIHOT 链接：https://aihot.virxact.com/items/cmtaxzs6k0d3croamopy7yjbg
- 原文链接：https://arxiv.org/abs/2608.25927

## AI 摘要

Code World Model 框架将世界演化与视觉呈现分离，由编码智能体生成可执行代码维护持久世界状态并执行规则一致的演化。该框架引入代理表示编码帧级时空约束并编译为代理视频，条件化视频模型渲染高保真视觉观察。微调后的 MiniMax-H3 能遵循编码智能体构建的交互世界中的代理时空规范，同时保留丰富视觉细节。

## 正文

World models aim to simulate how complex environments evolve under actions and events, yet existing video-based world models primarily learn dynamics from visual observations, which reveal outcomes rather than the underlying knowledge, rules, and mechanisms governing world evolution. This makes it difficult to maintain persistent consequences and support coherent, open-ended evolution. We introduce Code World Model, a framework that separates world evolution from visual realization by combining the reasoning and coding capabilities of language models with the generative priors of video models. A coding agent serves as the world brain, reasoning about events and their consequences and generating executable code to maintain persistent world state and perform rule-consistent evolution. To connect executable state with visual generation, we introduce a proxy representation that encodes frame-wise spatiotemporal constraints and is compiled into a proxy video, which conditions a video model to render high-fidelity visual observations. We further develop data pipelines for constructing aligned proxy-observation pairs from gameplay and real-world videos. After fine-tuning on paired gameplay data, MiniMax-H3 follows proxy-based spatiotemporal specifications from simple interactive worlds built by the coding agent while preserving rich visual details and dynamics. These results demonstrate the potential of combining code for persistent world evolution with video models for flexible visual realization, providing a new path toward open-ended world models.