MASS: Multiplayer World Models with Authoritative Shared State

TL;DR - MASS is an arXiv cs.CV preprint proposing a multiplayer video world model that separates a global, authoritative game state from per-view rendering, borrowing the server-client architecture of multiplayer games. It matters because it addresses the view-inconsistency and compute-redundancy failures that block current world models from scaling to many simultaneous agents.

• A learned Logic Engine advances a global typed state from joint actions with no hand-written transition function, serving as the sole recurrent memory and synchronization reference.
• A learned Rendering Engine decodes that shared state into independent, mutually consistent views for any requested camera on demand, decoupling world dynamics from view-dependent visual latents.
• On a matched multiplayer Snake benchmark, it reports higher state accuracy and lower cross-view inconsistency than state-of-the-art multi-view baselines.
• Scalability claim: simulation of 1,024 concurrent players over 10,000 recurrent steps, positioning explicit authoritative state as a foundation for multi-agent world simulation.