World Model-Based Planning

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49 papers in the last four weeks, up 145% on the four weeks before. 0.5% of all new papers.

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Latest papers 184

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PatchWorld: Gradient-Free Optimization of Executable World Models
May 29, 2026Jiaxin Bai, Yue Guo, Yifei Dong +13Belief-Space Planning World Model Learning
1Hong Kong Baptist University · 2Independent Researcher · 3HKUST +4
World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications
May 28, 2026Arif Hassan Zidan, Yi Pan, Hanqi Jiang +23World Model Learning World Model-Based Planning
School of Computer and Cyber Sciences, Augusta University, Augusta, GA, USA · School of Computing, University of Georgia, Athens, GA, USA · Tandon School of Engineering, New York University, Brooklyn, NY, USA +9
Physically Viable World Models: A Case for Query-Conditioned Embodied AI
May 28, 2026Adam J. Thorpe, Stepan Tretiakov, Cheng-Hsi Hsiao +6World Models for Robotics Causal World Models
The University of Texas at Austin
Latent Goal Prediction from Language for Model-Based Planning
May 26, 2026Samuel Barbeau, Simon Roy, Giovanni Beltrame +2World Model-Based Planning Long-Horizon Planning
1École de Technologie Supérieure, Montréal · 2International Laboratory on Learning Systems (ILLS) · 3Polytechnique Montréal +4
Back to Parsimonious Latents: Learning Task-Centric World Models from Visual Foundations
May 25, 2026Minghao Fu, Fan Feng, Nicklas Hansen +1World Model Learning World Models
University of California, San Diego
World Model Control by Trajectory Reachability Metrics
May 21, 2026Liangyu Li, Shengzhi Wang, Libin Qiu +2Reachability Analysis World Models for Robotics
Tongji University
Efficient Agentic Reasoning Through Self-Regulated Simulative Planning
May 21, 2026Mingkai Deng, Jinyu Hou, Lara Sá Neves +4LLM Planning World Model-Based Planning
Carnegie Mellon University · Institute of Foundation Models (IFM)
Robo-Cortex: A Self-Evolving Embodied Agent via Dual-Grain Cognitive Memory and Autonomous Knowledge Induction
May 18, 2026Nga Teng Chan, Yi Zhang, Yechi Liu +9Embodied Navigation World Model-Based Planning
1The Hong Kong University of Science and Technology · 2X-Humanoid · Institute of Automation, CAS +1
Learning Multi-Timescale Abstractions for Hierarchical Combinatorial Planning
May 16, 2026Vivienne Huiling Wang, Tinghuai Wang, Joni PajarinenWorld Model-Based Planning Hierarchical RL
Department of Electrical Engineering and Automation, Aalto University, Finland · Qutwo, Finland
Imperfect World Models are Exploitable
May 15, 2026Logan Mondal Bhamidipaty, Esmeralda S. Whitammer, David Abel +2Reward Hacking World Model-Based Planning
University of Edinburgh · Stanford University
Slot-MPC: Goal-Conditioned Model Predictive Control with Object-Centric Representations
May 14, 2026Jonathan Spieler, Angel Villar-Corrales, Sven BehnkeWorld Models for Robotics World Model-Based Planning
Autonomous Intelligent Systems, Computer Science Institute VI - Intelligent Systems and Robotics, Center for Robotics and the Lamarr Institute for Machine Learning and Artificial Intelligence, University of Bonn, Germany
EponaV2: Driving World Model with Comprehensive Future Reasoning
May 14, 2026Jiawei Xu, Zhizhou Zhong, Zhijian Shu +8World Model Learning World Model-Based Planning
1PCA Lab, VCIP, College of Computer Science, Nankai University · 2Horizon Robotics · 3HKUST +4
Do Enterprise Systems Need Learned World Models? The Importance of Context to Infer Dynamics
May 12, 2026Jishnu Sethumadhavan Nair, Patrice Bechard, Rishabh Maheshwary +14Distribution Shift World Model-Based Planning
1ServiceNow · 2Mila
The DAWN of World-Action Interactive Models
May 12, 2026Hongbo Lu, Liang Yao, Chenghao He +6Diffusion-Based Planning World Model-Based Planning
1COWARobot Co. Ltd · 2Shanghai Jiao Tong University · 3Hohai University
Latent Geometry Beyond Search: Amortizing Planning in World Models
May 9, 2026Hoang Nguyen, Xiaohao Xu, Xiaonan HuangWorld Model-Based Planning Model-Based Planning
Department of Robotics, University of Michigan, Ann Arbor
Is the Future Compatible? Diagnosing Dynamic Consistency in World Action Models
May 8, 2026Bo-Kai Ruan, Teng-Fang Hsiao, Ling Lo +1World Models for Robotics World Model-Based Planning
National Yang Ming Chiao Tung University
Predictive but Not Plannable: RC-aux for Latent World Models
May 8, 2026Wenyuan Li, Guang Li, Keisuke Maeda +2Reachability Analysis World Model-Based Planning
Hokkaido University
See Tomorrow, Act Today: Foresight-Driven Autonomous Driving
May 8, 2026Bozhou Zhang, Nan Song, Yuang Wang +3End-to-End Autonomous Driving World Models
School of Data Science, Fudan University · Shanghai Innovation Institute · Imperial College London +1
Reconstruction or Semantics? What Makes a Latent Space Useful for Robotic World Models
May 7, 2026Nilaksh, Saurav Jha, Artem Zholus +1World Model Learning World Models for Robotics
Chandar Research Lab · Mila – Quebec AI Institute · Polytechnique Montréal +1
HaM-World: Soft-Hamiltonian World Models with Selective Memory for Planning
May 7, 2026Haoyun Tang, Haodong Cui, Keyao Xu +2World Model Learning Latent Dynamics Modeling
1Xi’an Jiaotong University · 2Huazhong University of Science and Technology · 3Nankai University +1
TRAP: Tail-aware Ranking Attack for World-Model Planning
May 3, 2026Siyuan Duan, Ke Zhang, Xizhao LuoBackdoor Attacks World Model-Based Planning
Department of Computer Science and Technology, Soochow University Suzhou, China
Physically Native World Models: A Hamiltonian Perspective on Generative World Modeling
May 1, 2026Sen Cui, Jingheng MaLatent Dynamics Modeling World Models
Tsinghua University
Lifting Embodied World Models for Planning and Control
Apr 28, 2026Alex N. Wang, Trevor Darrell, Pavel Izmailov +2Robotic Control World Model-Based Planning
Computer Science, New York University · BAIR, UC Berkeley
The Global Neural World Model: Spatially Grounded Discrete Topologies for Action-Conditioned Planning
Apr 17, 2026Noureddine KermicheWorld Model Learning World Model-Based Planning
Western Digital Corporation, Irvine, CA, USA
Grounded World Model: Latent Planning with Language Goals
Apr 13, 2026Quanyi Li, Lan Feng, Haonan Zhang +4Zero-Shot Robotic Manipulation World Models for Robotics
EPFL · NUS
JEPA-Bisim: Learning Robust Visual Representations for Planning with Joint-Embedding Predictive World Models
Feb 20, 2026Leonardo F. Toso, Davit Shadunts, Yunyang Lu +5Visual Representation Learning World Models for Robotics
Department of Electrical Engineering, Columbia University, New York, USA. · Capital One, USA.
H-WM: Robotic Task and Motion Planning Guided by Hierarchical World Model
Feb 11, 2026Jinbang Huang, Wenyuan Chen, Zhiyuan Li +9Long-Horizon Robotic Manipulation World Models for Robotics
Huawei Noah’s Ark Lab · University of Toronto · University of British Columbia +1
Imagine-then-Plan: Agent Learning from Adaptive Lookahead with World Models
Jan 13, 2026Youwei Liu, Jian Wang, Hanlin Wang +2World Model-Based Planning Model-Based Planning
Central South University · Department of Computing, The Hong Kong Polytechnic University · College of Computer Science, Sichuan University
MobileDreamer: Generative Sketch World Model for GUI Agent
Jan 7, 2026Yilin Cao, Yufeng Zhong, Zhixiong Zeng +6Mobile GUI Automation World Model Learning
State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences · Meituan · School of Artificial Intelligence, University of Chinese Academy of Sciences
What Drives Success in Physical Planning with Joint-Embedding Predictive World Models?
Dec 30, 2025Basile Terver, Tsung-Yen Yang, Jean Ponce +2World Model-Based Planning Joint-Embedding Predictive Architecture
Meta FAIR · Inria Paris · Ecole normale supérieure / PSL +1

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PatchWorld: Gradient-Free Optimization of Executable World Models

Jiaxin Bai, Yue Guo, Yifei Dong, Jiaxuan Xiong+12

1Hong Kong Baptist University · 2Independent Researcher · 3HKUST+4

Belief-Space Planning World Model Learning World Models World Model-Based Planning Program Synthesis Model-Based Planning

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Text-agent environments are typically modeled as partially observable Markov decision processes (POMDPs), assuming that the simulator's latent state and transition dynamics are hidden from the agent. Yet little work has examined whether executable code can be induced to serve as a world model for prediction and planning under partial observability. We introduce PatchWorld, a gradient-free framework that turns offline trajectories into executable Python world models through counterexample-guided code repair. Instead of predicting the next observation with a black-box model, PatchWorld induces symbolic belief-state programs whose action updates can be inspected, replayed, and locally patched. Across seven AgentGym environments, PatchWorld-Simple achieves the highest code-based planning score among evaluated methods, reaching 76.4% macro success in live one-step lookahead while invoking no LLM calls inside the world-model prediction module itself. We further find that a human-specified residual-memory bias improves surface observation fidelity but weakens decision utility. This exposes a tradeoff in executable world models, since improving observation fidelity can come at the expense of action-discriminative dynamics, and vice versa. Code is available at https://github.com/HKBU-KnowComp/PatchWorld.

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