Multi-Agent Egocentric World Model with Fine-Grained Embodied Interaction

arXiv:2610.12299 · cs.CV, cs.AI · Submitted 2026-10-08 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-10-08

Updated: 2026-10-08

Project page: https://cvlab-kaist.github.io/ME-World

Terminology

• World Model — 77× in this paper · explained in 7 episodes
• Consistency — 44× in this paper · explained in 3 episodes
• Benchmark — 38× in this paper · explained in 2 episodes
• Alignment — 8× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 6× in this paper
• Transformer — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Adaptation — 4× in this paper · explained in 1 episode
• Cosine Similarity — 4× in this paper · explained in 3 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Rectified Flow — 2× in this paper · explained in 3 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Abstraction — 1× in this paper · explained in 1 episode
• Agent Architectures — 1× in this paper · explained in 1 episode
• Agentic Coding — 1× in this paper · explained in 1 episode
• Anchor Tokens — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Exponential Moving Average (EMA) — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Tokenization — 1× in this paper · explained in 2 episodes

Sources

• World Simulation with Video Foundation Models for Physical AI
• MASS: Multiplayer World Models with Authoritative Shared State
• Rhythm: Learning Interactive Whole-Body Control for Dual Humanoids
• HandsOnWorld: Unconstrained Egocentric Video Generation with Camera-Disentangled Hand Control
• DreamX-World 1.0: A General-Purpose Interactive World Model
• Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability
• YOLOX: Exceeding YOLO Series in 2021
• Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives
• E$^3$C: Video Generation with 3D Environmental Memory and Ego-Exo Human Pose Control
• EgoSim: Egocentric World Simulator for Embodied Interaction Generation
• Multiplayer Interactive World Models with Representation Autoencoders
• MetaWorld: Scaling Multi-Agent Video World Model from Single-view Video Data
• AnchorWorld: Embodied Egocentric World Simulation with View-based Evolution Customization
• Depth Anything 3: Recovering the Visual Space from Any Views
• Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players
• Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
• Decoupled Weight Decay Regularization
• Streaming Multi-Agent Autoregressive Diffusion Model with World State Registers
• Cosmos World Foundation Model Platform for Physical AI
• MultiGen: Level-Design for Editable Multiplayer Worlds in Diffusion Game Engines

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