From World Models to World Action Models: A Concise Tutorial for Robotics
On the map: World models → World models for language agents
Abstract (arXiv)
Rather than providing an exhaustive survey, this paper presents a concise tutorial on world models and world action models for robotics. After reading the tutorial, readers should have a clear understanding of what constitutes a "world", how world models and world action models are defined, and what roles they play within robotic AI systems. The tutorial also develops a unified perspective for comparing representative approaches, such as World Labs' spatial intelligence models, Yann LeCun's JEPA framework, and NVIDIA's Cosmos platform, and clarifies how these models differ in their representations, predictive capabilities, and interaction mechanisms.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in World models for language agents, one of 11 directions in World models. Builds on 50 of its 57 references that are in the map. First posted on arXiv 1 Jul 2026.
Builds on
50 of 57 references.
References · 50
- 2025Wan: Open and Advanced Large-Scale Video Generative Modelscited by 2,536
- 2018World Modelscited by 1,444
- 2023Mastering Diverse Domains through World Modelscited by 1,193
- 2025V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planningcited by 738
- 2023TD-MPC2: Scalable, Robust World Models for Continuous Controlcited by 482
- 2026World Action Models are Zero-shot Policiescited by 411
- 2025UniVLA: Learning to Act Anywhere with Task-centric Latent Actionscited by 386
- 2022DayDreamer: World Models for Physical Robot Learningcited by 372
- 2024DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planningcited by 357
- 2026Fast-WAM: Do World Action Models Need Test-time Future Imagination?cited by 311
- 2024GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulationcited by 290
- 2024Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representationscited by 279
38 more
- 2026Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planningcited by 274
- 2023Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Modelscited by 264
- 2026LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixelscited by 237
- 2025Motus: A Unified Latent Action World Modelcited by 231
- 2025Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasetscited by 218
- 2023Any-point Trajectory Modeling for Policy Learningcited by 207
- 2025Unified Video Action Modelcited by 195
- 2023Learning to Act from Actionless Videos through Dense Correspondencescited by 159
- 2025Ctrl-World: A Controllable Generative World Model for Robot Manipulationcited by 149
- 2025mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAscited by 133
- 2024Flow as the Cross-Domain Manipulation Interfacecited by 126
- 2026DreamDojo: A Generalist Robot World Model from Large-Scale Human Videoscited by 117
- 2025AdaWorld: Learning Adaptable World Models with Latent Actionscited by 108
- 2025Video Generators are Robot Policiescited by 86
- 2024Dreamitate: Real-World Visuomotor Policy Learning via Video Generationcited by 84
- 2025PhysTwin: Physics-Informed Reconstruction and Simulation of Deformable Objects from Videoscited by 78
- 2026DiT4DiT: Jointly Modeling Video Dynamics and Actions for Generalizable Robot Controlcited by 71
- 2025Vidar: Embodied Video Diffusion Model for Generalist Manipulationcited by 58
- 2024Closed-Loop Visuomotor Control with Generative Expectation for Robotic Manipulationcited by 51
- 2024VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planningcited by 37
- 20253DFlowAction: Learning Cross-Embodiment Manipulation from 3D Flow World Modelcited by 36
- 2025Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrationscited by 33
- 2025EmbodieDreamer: Advancing Real2Sim2Real Transfer for Policy Training via Embodied World Modelingcited by 29
- 2025ParticleFormer: A 3D Point Cloud World Model for Multi-Object, Multi-Material Robotic Manipulationcited by 26
- 2024Grounding Video Models to Actions through Goal Conditioned Explorationcited by 25
- 2025LaDi-WM: A Latent Diffusion-based World Model for Predictive Manipulationcited by 24
- 2025Inference-Time Enhancement of Generative Robot Policies via Predictive World Modelingcited by 22
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- 2025SKIL: Semantic Keypoint Imitation Learning for Generalizable Data-efficient Manipulationcited by 21
- 2025FlowDreamer: A RGB-D World Model with Flow-based Motion Representations for Robot Manipulationcited by 17
- 2025Object-Centric World Model for Language-Guided Manipulationcited by 16
- 2025OSVI-WM: One-Shot Visual Imitation for Unseen Tasks using World-Model-Guided Trajectory Generationcited by 10
- 2025WoMAP: World Models For Embodied Open-Vocabulary Object Localizationcited by 8
- 2025ExoPredicator: Learning Abstract Models of Dynamic Worlds for Robot Planningcited by 8
- 2026ContactGaussian-WM: Learning Physics-Grounded World Model from Videoscited by 7
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- 2026SSI-Policy: Learning Structured Scene Interfaces for Vision-Language Robotic Manipulationcited by 1
Built on by
Citing papers per year: 2026: 3.
3 papers.
- 2026PredVLA: Predictive Sensorimotor Modeling for Sub-Million-Parameter Robot Manipulationcited by 0
- 2026Valerant: An Automatic Navigable Game Map Generator via Action-Conditioned World Model Explorationcited by 0
- 2026DualWAM: Dual-System World Action Models for Asynchronous Global Planning and Local Refinementcited by 0
- 2026DualWAM: Dual-System World Action Models for Asynchronous Global Planning and Local Refinement21 Sep 2026
- 2026Valerant: An Automatic Navigable Game Map Generator via Action-Conditioned World Model Exploration8 Sep 2026
- 2026PredVLA: Predictive Sensorimotor Modeling for Sub-Million-Parameter Robot Manipulation27 Aug 2026
Similar, not cited
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