mlsanityData to 7 Oct 2026

World Models

arXiv 1803.10122 ↗First posted 27 Mar 2018cs.LG stat.MLcited by 1,444

On the map: World models → Latent dynamics models and model-based RL

Abstract (arXiv)

We explore building generative neural network models of popular reinforcement learning environments. Our world model can be trained quickly in an unsupervised manner to learn a compressed spatial and temporal representation of the environment. By using features extracted from the world model as inputs to an agent, we can train a very compact and simple policy that can solve the required task. We can even train our agent entirely inside of its own hallucinated dream generated by its world model, and transfer this policy back into the actual environment. An interactive version of this paper is available at https://worldmodels.github.io/

Key facts. Cited by 1,444 papers in the map (data through 7 Oct 2026). Placed in Latent dynamics models and model-based RL, one of 11 directions in World models. Builds on 2 of its 156 references that are in the map. First posted on arXiv 27 Mar 2018.

Builds on

2 of 156 references.

Closest ancestors · 2

Same direction, newest first

  1. 2017Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning8 Aug
  2. 2015On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models30 Nov

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2018: 3; 2019: 7; 2020: 8; 2021: 89; 2022: 94; 2023: 92; 2024: 168; 2025: 336; 2026: 647.

1,444 papers.

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  1. 2019Dream to Control: Learning Behaviors by Latent Imaginationcited by 1,598
  2. 2018Learning Latent Dynamics for Planning from Pixelscited by 1,221
  3. 2023Mastering Diverse Domains through World Modelscited by 1,193
  4. 2020Mastering Atari with Discrete World Modelscited by 990
  5. 2024WorldSimBench: Towards Video Generation Models as World Simulatorscited by 867
  6. 2023Reasoning with Language Model is Planning with World Modelcited by 846
  7. 2025Cosmos World Foundation Model Platform for Physical AIcited by 833
  8. 2025V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planningcited by 738
  9. 2020MOPO: Model-based Offline Policy Optimizationcited by 630
  10. 2021Implicit Behavioral Cloningcited by 442
  11. 2020Planning to Explore via Self-Supervised World Modelscited by 365
  12. 2024The Platonic Representation Hypothesiscited by 362
38 more
  1. 2024DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planningcited by 357
  2. 2025WorldVLA: Towards Autoregressive Action World Modelcited by 351
  3. 2024GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulationcited by 290
  4. 2024Diffusion Models Are Real-Time Game Enginescited by 282
  5. 2024Navigation World Modelscited by 262
  6. 2022Contrastive Learning as Goal-Conditioned Reinforcement Learningcited by 241
  7. 2022Diffusion Probabilistic Modeling for Video Generationcited by 237
  8. 2026LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixelscited by 237
  9. 2023OccWorld: Learning a 3D Occupancy World Model for Autonomous Drivingcited by 230
  10. 2021A Survey of Human-in-the-loop for Machine Learningcited by 214
  11. 2021Towards Causal Representation Learningcited by 207
  12. 2025World Simulation with Video Foundation Models for Physical AIcited by 183
  13. 2021Character Controllers Using Motion VAEscited by 182
  14. 2024Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AIcited by 175
  15. 2022Masked World Models for Visual Controlcited by 169
  16. 2024Understanding World or Predicting Future? A Comprehensive Survey of World Modelscited by 161
  17. 2025WorldMem: Long-term Consistent World Simulation with Memorycited by 152
  18. 2024Tree Search for Language Model Agentscited by 148
  19. 2023Structured World Models from Human Videoscited by 144
  20. 2026Advancing Open-source World Modelscited by 144
  21. 2022TransDreamer: Reinforcement Learning with Transformer World Modelscited by 143
  22. 2018Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guaranteescited by 138
  23. 2026Cosmos 3: Omnimodal World Models for Physical AIcited by 137
  24. 2022GAUDI: A Neural Architect for Immersive 3D Scene Generationcited by 136
  25. 2021Unconstrained Scene Generation with Locally Conditioned Radiance Fieldscited by 130
  26. 2025Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulationcited by 129
  27. 2025Unified Vision-Language-Action Modelcited by 128
  28. 2025Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systemscited by 125
  29. 2024GameGen-X: Interactive Open-world Game Video Generationcited by 124
  30. 2025Cambrian-S: Towards Spatial Supersensing in Videocited by 123
  31. 2025Training Agents Inside of Scalable World Modelscited by 122
  32. 2021Pathdreamer: A World Model for Indoor Navigationcited by 117
  33. 2024Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigationcited by 116
  34. 2025Epona: Autoregressive Diffusion World Model for Autonomous Drivingcited by 115
  35. 2022Generating Long Videos of Dynamic Scenescited by 113
  36. 2025Agentic Large Language Models, a surveycited by 105
  37. 2026V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learningcited by 104
  38. 2024DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformerscited by 96

50 most cited of 1,444 All 1,444 (JSON)

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  1. 2018Recurrent World Models Facilitate Policy Evolution
  2. 2021Dropout's Dream Land: Generalization from Learned Simulators to Reality
  3. 2025Language-conditioned world model improves policy generalization by reading environmental descriptions
  4. 2025Multimodal Dreaming: A Global Workspace Approach to World Model-Based Reinforcement Learning
  5. 2024Open-World Reinforcement Learning over Long Short-Term Imagination
  6. 2024Masked Generative Priors Improve World Models Sequence Modelling Capabilities
  7. 2023Facing Off World Model Backbones: RNNs, Transformers, and S4
  8. 2020Smaller World Models for Reinforcement Learning