MultiWorld: Scalable Multi-Agent Multi-View Video World Models
Summary
MultiWorld is a unified framework for multi-agent multi-view video world modeling that achieves accurate control of multiple agents while maintaining multi-view consistency through a Multi-Agent Condition Module and Global State Encoder.
View Cached Full Text
Cached at: 04/21/26, 07:20 AM
Paper page - MultiWorld: Scalable Multi-Agent Multi-View Video World Models
Source: https://huggingface.co/papers/2604.18564
Abstract
MultiWorld is a unified framework for multi-agent multi-view world modeling that achieves accurate multi-agent control while maintaining multi-view consistency through specialized modules for condition handling and global state encoding.
Video world modelshave achieved remarkable success in simulating environmental dynamics in response to actions by users or agents. They are modeled asaction-conditioned video generationmodels that take historical frames and current actions as input to predict future frames. Yet, most existing approaches are limited to single-agent scenarios and fail to capture the complex interactions inherent in real-worldmulti-agent systems. We present MultiWorld, a unified framework for multi-agent multi-view world modeling that enables accurate control of multiple agents while maintainingmulti-view consistency. We introduce theMulti-Agent Condition Moduleto achieve precise multi-agent controllability, and theGlobal State Encoderto ensure coherent observations across different views. MultiWorld supports flexible scaling of agent and view counts, and synthesizes different views in parallel for high efficiency. Experiments on multi-player game environments and multi-robot manipulation tasks demonstrate that MultiWorld outperforms baselines in video fidelity, action-following ability, andmulti-view consistency. Project page: https://multi-world.github.io/
View arXiv pageView PDFProject pageGitHub4Add to collection
Get this paper in your agent:
hf papers read 2604\.18564
Don’t have the latest CLI?curl \-LsSf https://hf\.co/cli/install\.sh \| bash
Models citing this paper0
No model linking this paper
Cite arxiv.org/abs/2604.18564 in a model README.md to link it from this page.
Datasets citing this paper0
No dataset linking this paper
Cite arxiv.org/abs/2604.18564 in a dataset README.md to link it from this page.
Spaces citing this paper0
No Space linking this paper
Cite arxiv.org/abs/2604.18564 in a Space README.md to link it from this page.
Collections including this paper0
No Collection including this paper
Add this paper to acollectionto link it from this page.
Similar Articles
MASS: Multiplayer World Models with Authoritative Shared State
This paper introduces MASS, a method for multiplayer world models that disentangles world dynamics from view rendering using an authoritative shared state, enabling scalable and consistent multi-agent simulation with up to 1,024 concurrent players.
Streaming Multi-Agent Autoregressive Diffusion Model with World State Registers
WorldWeaver (W²) introduces cross-agent world state registers to multi-agent video diffusion models, enabling shared world state persistence across agents and views, improving logical consistency in two-agent Minecraft video generation.
Multi-Agent World Models (3 minute read)
γ-World is a generative multi-agent world model that supports independently controllable, permutation-symmetric agents using Simplex Rotary Agent Encoding and Sparse Hub Attention, achieving real-time 24 FPS rollouts and zero-shot generalization from two to four players.
UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models
Introduces UniWorld-View, a unified framework for large-baseline novel view synthesis from monocular inputs, integrating occlusion-aware point cloud rendering with video diffusion models for precise camera control and geometric consistency.
Infinite Worlds with Versatile Interactions
This paper introduces LingBot-World 2.0, an advanced world modeling system with unbounded interaction horizons, real-time 720p 60fps video generation, diverse interactive elements (e.g., attacking, spell-casting), and novel multi-agent behavior control via pilot and director agents, along with a shared multi-player interface.