MultiGen: Level-Design for Editable Multiplayer Worlds in Diffusion Game Engines
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866910087053836288 |
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| author | Po, Ryan Zhang, David Junhao Hertz, Amir Wetzstein, Gordon Wadhwa, Neal Ruiz, Nataniel |
| author_facet | Po, Ryan Zhang, David Junhao Hertz, Amir Wetzstein, Gordon Wadhwa, Neal Ruiz, Nataniel |
| contents | Video world models have shown immense promise for interactive simulation and entertainment, but current systems still struggle with two important aspects of interactivity: user control over the environment for reproducible, editable experiences, and shared inference where players hold influence over a common world. To address these limitations, we introduce an explicit external memory into the system, a persistent state operating independent of the model's context window, that is continually updated by user actions and queried throughout the generation roll-out. Unlike conventional diffusion game engines that operate as next-frame predictors, our approach decomposes generation into Memory, Observation, and Dynamics modules. This design gives users direct, editable control over environment structure via an editable memory representation, and it naturally extends to real-time multiplayer rollouts with coherent viewpoints and consistent cross-player interactions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_06679 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | MultiGen: Level-Design for Editable Multiplayer Worlds in Diffusion Game Engines Po, Ryan Zhang, David Junhao Hertz, Amir Wetzstein, Gordon Wadhwa, Neal Ruiz, Nataniel Artificial Intelligence Computer Vision and Pattern Recognition Graphics Video world models have shown immense promise for interactive simulation and entertainment, but current systems still struggle with two important aspects of interactivity: user control over the environment for reproducible, editable experiences, and shared inference where players hold influence over a common world. To address these limitations, we introduce an explicit external memory into the system, a persistent state operating independent of the model's context window, that is continually updated by user actions and queried throughout the generation roll-out. Unlike conventional diffusion game engines that operate as next-frame predictors, our approach decomposes generation into Memory, Observation, and Dynamics modules. This design gives users direct, editable control over environment structure via an editable memory representation, and it naturally extends to real-time multiplayer rollouts with coherent viewpoints and consistent cross-player interactions. |
| title | MultiGen: Level-Design for Editable Multiplayer Worlds in Diffusion Game Engines |
| topic | Artificial Intelligence Computer Vision and Pattern Recognition Graphics |
| url | https://arxiv.org/abs/2603.06679 |