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OverSeer: Multi-Agent World Models Beyond What Agents See

Rui Li, Kam Woh Ng, Minghao Chen, Junlin Han, Jianyuan Wang, Zhaochong An, Juan-Manuel Pérez-Rúa, Andrea Vedaldi, Shikun Liu · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.28554 · cited by 0 works (OpenAlex) · open-access PDF

Chinese

尽管视频世界模型成功,但将其扩展到多个代理人是困难的,因为它需要生成几个代理人特定的视频流,在时间和代理人之间是一致的。为了解决这个差距,我们引入了OverSeer,一个多代理人世界模型,通过辅助摄像头视图来增加自我中心的代理人视图。我们建议,通过在空间中固定辅助视图,它们作为世界中心的代表作用:与代理人的视图不同,因为代理人位置的简单变化完全可以改变,辅助视图的变化直接地图到世界状态的本地化变化。我们表明,这些固定的视图在很大程度上有助于模型保持一致性。我们还表明,由于其冗余和半静态的性质,辅助视图可以通过Delta-VAE高效地压缩,

Machine translation (Meta M2M100); the English original follows.

Abstract

Despite the success of video world models, extending them to multiple agents is difficult because it requires generating several agent-specific video streams that are consistent in time and between agents. To address this gap, we introduce OverSeer, a multi-agent world model that augments egocentric agent views with auxiliary camera views. We suggest that, by fixing the auxiliary views in space, they act as a proxy for a world-centric representation: Unlike the agents' views, which can change entirely due to a simple change in agent position, changes in the auxiliary views directly map to localized changes in the world state. We show that these fixed views substantially help the model to maintain consistency. We also show that, due to their redundant and semi-static nature, the auxiliary views can be efficiently compressed with a delta-VAE that encodes only the changes relative to a static reference image, reducing the number of tokens required to process them. Experiments in Minecraft and Doom demonstrate improved world and agent consistency, with qualitative results on real-world multi-camera captures indicating that the approach is not tied to game engines. Our compression analysis further shows that delta-VAE substantially reduces the computational overhead of auxiliary-view generation. We conclude that these fixed views provide a simple and efficient way to improve multi-agent world models.

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Topics: Computer science, Simple (philosophy), Process (computing), Overhead (engineering), Real world data, Proxy (statistics)

Sources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange