Code Plans, Diffusion Renders: Open-Ended Generative World Modeling

arXiv:2609.26458 · cs.CV · Submitted 2026-09-22 · Read on arXiv

cs.CV

Submitted: 2026-09-22

Updated: 2026-09-22

Terminology

• World Model — 53× in this paper · explained in 7 episodes
• Diffusion Model — 10× in this paper · explained in 8 episodes
• Consistency — 9× in this paper · explained in 3 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Diffusion Models — 6× in this paper · explained in 6 episodes
• Conference on Computer Vision and Pattern Recognition — 5× in this paper
• CVF International Conference on Computer Vision — 4× in this paper
• Action Space — 3× in this paper · explained in 1 episode
• Fidelity — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Modeling — 2× in this paper · explained in 3 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• European Conference on Computer Vision — 1× in this paper
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Hybrid System — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Physical Constraints — 1× in this paper · explained in 7 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Self-Distillation — 1× in this paper · explained in 7 episodes

Sources

• AlayaWorld: Interactive Long-Horizon World Modeling - Full Technical Report (v1.1)
• MASS: Multiplayer World Models with Authoritative Shared State
• ShadowDancer: Teaching Video World Models Any Action by Learning Unified Dynamics Representations from a Video and Its Shadow
• Video Models as Native 4D Renderers: World-Grounded Conditioning from Animated Mesh
• DeepVerse: 4D Autoregressive Video Generation as a World Model
• Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models
• DreamX-World 1.0: A General-Purpose Interactive World Model
• LOME: Learning Human-Object Manipulation with Action-Conditioned Egocentric World Model
• Infinite Worlds with Versatile Interactions
• MineWorld: a Real-Time and Open-Source Interactive World Model on Minecraft
• Matrix-game 2.0: An open-source, real-time, and streaming interactive world model
• RELIC: Interactive Video World Model with Long-Horizon Memory
• Multiplayer Interactive World Models with Representation Autoencoders
• MetaWorld: Scaling Multi-Agent Video World Model from Single-view Video Data
• Memory Forcing: Spatio-Temporal Memory for Consistent Scene Generation on Minecraft
• ABot-World-0: Infinite Interactive World Rollout on a Single Desktop GPU
• Hunyuan-GameCraft: High-dynamic Interactive Game Video Generation with Hybrid History Condition
• AnchorWorld: Embodied Egocentric World Simulation with View-based Evolution Customization
• Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players

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