Vid2World: Crafting Video Diffusion Models to Interactive World Models
On the map: World models → Video-generation world models and simulators
also in 1 more
Abstract (arXiv)
World models, which predict future transitions from past observation and action sequences, have shown great promise for improving data efficiency in sequential decision-making. However, existing world models often require extensive domain-specific training and still produce low-fidelity, coarse predictions, limiting their usefulness in complex environments. In contrast, video diffusion models trained on large-scale internet data have demonstrated impressive capabilities in generating high-quality videos that capture diverse real-world dynamics. In this work, we present Vid2World, a general approach for leveraging and transferring pre-trained video diffusion models into interactive world models. To bridge the gap, Vid2World systematically explores video diffusion causalization, reshaping both the architecture and training objective of pre-trained models to enable autoregressive generation. Additionally, it incorporates a causal action guidance mechanism to enhance action controllability in the resulting interactive world models. Extensive experiments across multiple domains, including robot manipulation, 3D game simulation, and open-world navigation, demonstrate that our method offers a scalable and effective pathway for repurposing highly capable video diffusion models into interactive world models.
Key facts. Cited by 76 papers in the map (data through 14 Oct 2026). Placed in Video-generation world models and simulators, one of 11 directions in World models. Builds on 59 of its 82 references that are in the map. First posted on arXiv 20 May 2025.
Builds on
59 of 82 references.
Closest ancestors · 10
Same direction, newest first
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- 2025GameFactory: Creating New Games with Generative Interactive Videos14 Jan
- 2024AVID: Adapting Video Diffusion Models to World Models1 Oct
- 2024Genie: Generative Interactive Environments23 Feb
- 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets25 Nov
- 2023Learning Interactive Real-World Simulators9 Oct
- 2022Scalable Diffusion Models with Transformers19 Dec
- 2021Learning Transferable Visual Models From Natural Language Supervision26 Feb
- 2020Score-Based Generative Modeling through Stochastic Differential Equations26 Nov
- 2020Denoising Diffusion Probabilistic Models19 Jun
Other references · 49
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
- 2023GPT-4 Technical Reportcited by 18,396
- 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
- 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
- 2020Denoising Diffusion Implicit Modelscited by 9,781
- 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
- 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
- 2022Classifier-Free Diffusion Guidancecited by 5,847
- 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,503
- 2021On the Opportunities and Risks of Foundation Modelscited by 4,033
- 2022Video Diffusion Modelscited by 2,305
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- 2023Consistency Modelscited by 1,822
- 2023VBench: Comprehensive Benchmark Suite for Video Generative Modelscited by 1,822
- 2019Dream to Control: Learning Behaviors by Latent Imaginationcited by 1,653
- 2023AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuningcited by 1,433
- 2018Towards Accurate Generative Models of Video: A New Metric & Challengescited by 1,234
- 2025Cosmos World Foundation Model Platform for Physical AIcited by 864
- 2023Reasoning with Language Model is Planning with World Modelcited by 861
- 2018Recurrent World Models Facilitate Policy Evolutioncited by 785
- 2024Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusioncited by 681
- 2024LTX-Video: Realtime Video Latent Diffusioncited by 581
- 2025Mean Flows for One-step Generative Modelingcited by 561
- 2023VideoCrafter1: Open Diffusion Models for High-Quality Video Generationcited by 535
- 2024Evaluating Real-World Robot Manipulation Policies in Simulationcited by 495
- 2023DynamiCrafter: Animating Open-domain Images with Video Diffusion Priorscited by 471
- 2024From Slow Bidirectional to Fast Autoregressive Video Diffusion Modelscited by 433
- 2023DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Datacited by 337
- 2023Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Drivingcited by 319
- 2023Common Diffusion Noise Schedules and Sample Steps are Flawedcited by 310
- 2024Diffusion for World Modeling: Visual Details Matter in Ataricited by 300
- 2024Navigation World Modelscited by 272
- 2025Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasetscited by 240
- 2024RoboDreamer: Learning Compositional World Models for Robot Imaginationcited by 195
- 2025Open-Sora 2.0: Training a Commercial-Level Video Generation Model in 200kcited by 163
- 2024iVideoGPT: Interactive VideoGPTs are Scalable World Modelscited by 146
- 2021Rapid Exploration for Open-World Navigation with Latent Goal Modelscited by 121
- 2025AdaWorld: Learning Adaptable World Models with Latent Actionscited by 114
- 2023Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusioncited by 106
- 2025TesserAct: Learning 4D Embodied World Modelscited by 94
- 2023Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligencecited by 56
- 2024Can Language Models Serve as Text-Based World Simulators?cited by 52
- 2021Counter-Strike Deathmatch with Large-Scale Behavioural Cloningcited by 50
- 2025Pre-Trained Video Generative Models as World Simulatorscited by 44
- 2025Text2World: Benchmarking Large Language Models for Symbolic World Model Generationcited by 26
- 2020Neural Game Engine: Accurate learning of generalizable forward models from pixelscited by 12
- 2024Language Agents Meet Causality -- Bridging LLMs and Causal World Modelscited by 9
- 2025Trajectory World Models for Heterogeneous Environmentscited by 4
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Citing papers per year: 2025: 12; 2026: 64.
76 papers.
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By area:
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50 most cited of 76 All 76 (JSON)
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- 2026FutureWorlds: Learning Robotic World Models from Alternative Futures1 Oct 2026
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- 2026ACWM-Phys: Investigating Generalized Physical Interaction in Action-Conditioned Video World Models9 May 2026
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50 newest of 76 All 76 (JSON)
- 2026DreamDojo: A Generalist Robot World Model from Large-Scale Human Videoscited by 135
- 2025RELIC: Interactive Video World Model with Long-Horizon Memorycited by 96
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- 2025A Survey: Learning Embodied Intelligence from Physical Simulators and World Modelscited by 51
- 2026World Model for Robot Learning: A Comprehensive Surveycited by 46
- 2025Astra: General Interactive World Model with Autoregressive Denoisingcited by 33
- 2026Qwen-AgentWorld: Language World Models for General Agentscited by 28
- 2026MultiWorld: Scalable Multi-Agent Multi-View Video World Modelscited by 23
- 2026Reconstruction or Semantics? What Makes a Latent Space Useful for Robotic World Modelscited by 22
- 2026BridgeV2W: Bridging Video Generation Models to Embodied World Models via Embodiment Maskscited by 20
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- 2026Addressable Memory for Video World Modelscited by 15
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- 2026PAWA: Panoramic Action-conditioned World Modeling for Multiple Agents14 Oct 2026
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- 2026Action Jets: Learning the Local Shape of the Action-conditioned Data Manifold13 Oct 2026
- 2026GLIMPSE: Global-Local Indexing with Multi-Precision Spectral Encoding for Explorable Video World Models9 Oct 2026
- 2026EVEWorld: Physical Evolution Supervision for Embodied World Models2 Oct 2026
- 2026FutureWorlds: Learning Robotic World Models from Alternative Futures1 Oct 2026
- 2026OneWorld: Learning Consistent Physics Across Actions in World Models25 Sep 2026
- 2026Action Forcing: Training World Models on Unsupervised Video by Recovering Underlying Egomotion Bases24 Sep 2026
- 2026CausalWM: Causal Chain-of-Thought Reasoning for Embodied World Model19 Sep 2026
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- 2026VGI-Bench: Probing Visual Intelligence in Video Generation Models20 Aug 2026
- 2026LLM-as-a-Verifier: A General-Purpose Verification Framework6 Jul 2026
- 2026Generation Models Know Space: Unleashing Implicit 3D Priors for Scene Understanding19 Mar 2026
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- 2026VIS-Ground: Video Interactive Storytelling with Contextual Grounding7 Oct 2026
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- 2026World Simulator: Queer Erotica and the Absurdity of AI Video Models That Promise the World29 Jun 2026
- 2026FashionChameleon: Towards Real-Time and Interactive Human-Garment Video Customization15 May 2026
- 2026From Imagined Futures to Executable Actions: Mixture of Latent Actions for Robot Manipulation12 May 2026
- 2026PhysVid: Physics Aware Local Conditioning for Generative Video Models27 Mar 2026
- 2025The World is Your Canvas: Painting Promptable Events with Reference Images, Trajectories, and Text18 Dec 2025
- 2025KlingAvatar 2.0 Technical Report15 Dec 2025
- 2025PhyDetEx: Detecting and Explaining the Physical Plausibility of T2V Models1 Dec 2025
- 2025In-Video Instructions: Visual Signals as Generative Control24 Nov 2025
- 2025MATRIX: Mask Track Alignment for Interaction-aware Video Generation8 Oct 2025
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