World Model Evaluation

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World Model Evaluation studies whether a model captures how an environment changes, especially when an agent acts or observations are missing. Approaches include open-loop prediction metrics, action-conditioned rollouts, closed-loop policy tests, physics-grounded diagnostics, and human or vision-language model judging. Benchmarks span robotic manipulation such as LIBERO and RoboTwin, driving such as NuPlan, and interactive GUI, web, and game environments. A central challenge is that visual realism and one-step accuracy often fail to predict physical consistency, long-term reliability, or planning success, so evaluation remains fragmented across tasks and horizons.

Latest papers

212 papers49 papers in the last four weeks, up 75% on the four weeks before. 0.3% of all new papers.

Is Your Driving World Model an All-Around Player?
May 11, 2026Lingdong Kong, Ao Liang, Tianyi Yan +20Autonomous Driving Benchmarks Physical Consistency in Video Generation
NUS · UM · USTC +10
PhyGround: Benchmarking Physical Reasoning in Generative World Models
May 11, 2026Juyi Lin, Arash Akbari, Yumei He +13Physical Consistency in Video Generation World Model Evaluation
1Northeastern University · 2Tulane University · University of Washington +1
WorldReasonBench: Human-Aligned Stress Testing of Video Generators as Future World-State Predictors
May 11, 2026Keming Wu, Yijing Cui, Wenhan Xue +11World Models Video Reasoning
Tsinghua University · Nanyang Technological University · Hong Kong University of Science and Technology (Guangzhou) +2
How Mobile World Model Guides GUI Agents?
May 11, 2026Weikai Xu, Kun Huang, Yunren Feng +10World Model Learning GUI Agents
1Nanyang Technological University · 2MiLM Plus, Xiaomi Inc. · 3Independent Researchers +3
ACWM-Phys: Investigating Generalized Physical Interaction in Action-Conditioned Video World Models
May 9, 2026Haotian Xue, Yipu Chen, Liqian Ma +4Action-Conditioned Video Generation World Models
Georgia Institute of Technology
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
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
LoViF 2026 The First Challenge on Holistic Quality Assessment for 4D World Model (PhyScore)
May 6, 2026Wei Luo, Yiting Lu, Xin Li +32Physical Consistency in Video Generation Anomaly Localization
iWorld-Bench: A Benchmark for Interactive World Models with a Unified Action Generation Framework
May 5, 2026Jianjie Fang, Yingshan Lei, Qin Wan +8World Model Evaluation Interactive World Models
Tsinghua University, China · Northeastern University, China · South China University of Technology, China
RoboAlign-R1: Distilled Multimodal Reward Alignment for Robot Video World Models
May 5, 2026Hao Wu, Yuqi Li, Yuan Gao +10Multimodal Reward Modeling World Model Evaluation
Tencent · Tsinghua University · Department of Computer Science, City University of New York +3
Latent State Design for World Models under Sufficiency Constraints
May 3, 2026Keon Woo KimRepresentation Learning Predictive Representation Learning
Om Labs
Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond
Apr 24, 2026Meng Chu, Xuan Billy Zhang, Kevin Qinghong Lin +47World Model Learning Action-Conditioned World Models
dWorldEval: Scalable Robotic Policy Evaluation via Discrete Diffusion World Model
Apr 24, 2026Yaxuan Li, Zhongyi Zhou, Yefei Chen +2World Models for Robotics Robotic Policy Evaluation
Current Robotics · University of Toronto
WorldMark: A Unified Benchmark Suite for Interactive Video World Models
Apr 23, 2026Xiaojie Xu, Zhengyuan Lin, Kang He +5Action-Conditioned World Models World Model Evaluation
Alaya Studio, Shanda AI Research Tokyo · The University of Tokyo · Shanghai Innovation Institute
RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation
Apr 21, 2026Feng Jiang, Yang Chen, Kyle Xu +8Robotic Manipulation Robot Manipulation Benchmarks
Peking University · Tsinghua University · Lightwheel
Beyond State Consistency: Behavior Consistency in Text-Based World Models
Apr 15, 2026Youling Huang, Guanqiao Chen, Junchi Yao +8World Models World Model Learning
Dalian University of Technology · Microsoft · MBZUAI +1
MotionScape: A Motion-Stratified UAV Video Benchmark for World Modeling and Future Video Generation
Apr 9, 2026Zile Guo, Zhan Chen, Xiaoxuan Liu +5Aerial Robotics Video Generation
Aerospace Information Research Institute, Chinese Academy of Sciences · Key Laboratory of Target Cognition and Application Technology, Chinese Academy of Sciences · School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences +1
World Action Verifier: Self-Improving World Models via Forward-Inverse Asymmetry
Apr 2, 2026Yuejiang Liu, Fan Feng, Lingjing Kong +6World Models for Robotics Action-Conditioned World Models
Stanford University · UC San Diego · Carnegie Mellon University +2
ICAT: Incident-Case-Grounded Adaptive Testing for Physical-Risk Prediction in Embodied World Models
Mar 31, 2026Zhenglin Lai, Sirui Huang, Yuteng Li +3AI Safety Evaluation World Model Evaluation
Shenzhen University, Shenzhen, China.
World Reasoning Arena
Mar 26, 2026PAN Team, Qiyue Gao, Kun Zhou +15World Model Evaluation World Model-Based Planning
Institute of Foundation Models, Mohamed bin Zayed University of Artificial Intelligence
WildWorld: A Large-Scale Dataset for Dynamic World Modeling with Actions and Explicit State toward Generative ARPG
Mar 24, 2026Zhen Li, Zian Meng, Shuwei Shi +5World Model Learning World Models
Alaya Studio, Shanda AI Research Tokyo · Beijing Institute of Technology · Shenzhen MSU-BIT University +2
Omni-WorldBench: Towards a Comprehensive Interaction-Centric Evaluation for World Models
Mar 23, 2026Meiqi Wu, Zhixin Cai, Fufangchen Zhao +13World Model Evaluation Interactive World Models
School of Computer Science and Technology, UCAS · The Key Laboratory of Cognition and Decision Intelligence for Complex Systems, CASIA · AMAP, Alibaba Group +2
Do World Action Models Generalize Better than VLAs? A Robustness Study
Mar 23, 2026Zhanguang Zhang, Zhiyuan Li, Behnam Rahmati +11World Action Models Robustness of VLA Models
Huawei Technologies · University of Toronto
Out of Sight, Out of Mind? Evaluating State Evolution in Video World Models
Mar 13, 2026Ziqi Ma, Mengzhan Liufu, Georgia GkioxariVideo World Models World Model Evaluation
California Institute of Technology
Latent World Models for Automated Driving: A Unified Taxonomy, Evaluation Framework, and Open Challenges
Mar 10, 2026Rongxiang Zeng, Yongqi DongWorld Models for Autonomous Driving World Model Evaluation
RWTH Aachen University, Templergraben 55, 52062 Aachen, Germany · Delft University of Technology, 2628 CN Delft, The Netherlands
Specification-Driven Generation and Evaluation of Discrete-Event World Models via the DEVS Formalism
Mar 4, 2026Zheyu Chen, Huiteng Zhuang, Zhuohuan Li +1LLM World Models World Model Evaluation
Zhili College, Tsinghua University · School of Transportation Science and Engineering, Beihang University · Department of Industrial Engineering, Tsinghua University
The Trinity of Consistency as a Defining Principle for General World Models
Feb 26, 2026Jingxuan Wei, Siyuan Li, Yuhang Xu +21World Models World Model Learning
WebWorld: A Large-Scale World Model for Web Agent Training
Feb 16, 2026Zikai Xiao, Jianhong Tu, Chuhang Zou +7LLM World Models World Model Learning
Qwen Team, Alibaba Group · Zhejiang University
OccStress: Stress-Testing the 4D Occupancy Forecasting Chain
Dec 17, 2025Yu Zheng, Jie Hu, Jiaqi Xiong +4Forecasting Benchmarks 3D Occupancy Prediction
Hunan University · ETH Zurich
MobileWorldBench: Towards Semantic World Modeling For Mobile Agents
Dec 16, 2025Shufan Li, Konstantinos Kallidromitis, Akash Gokul +3World Models Mobile GUI Agents
UCLA · Panasonic AI Research · Salesforce AI Research

May 11, 2026J/K move · Enter open · S save

Is Your Driving World Model an All-Around Player?

Lingdong Kong, Ao Liang, Tianyi Yan, Hongsi Liu+19

NUS · UM · USTC+10

Autonomous Driving Benchmarks Physical Consistency in Video Generation World Models for Autonomous Driving World Model Evaluation Video World Models

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Today's driving world models can generate remarkably realistic dash-cam videos, yet no single model excels universally. Some generate photorealistic textures but violate basic physics; others maintain geometric consistency but fail when subjected to closed-loop planning. This disconnect exposes a critical gap: the field evaluates how real generated worlds appear, but rarely whether they behave realistically. We introduce WorldLens, a unified benchmark that measures world-model fidelity across the full spectrum, from pixel quality and 4D geometry to closed-loop driving and human perceptual alignment, through five complementary aspects and 24 standardized dimensions. Our evaluation of six representative models reveals that no existing approach dominates across all axes: texture-rich models violate geometry, geometry-aware models lack behavioral fidelity, and even the strongest performers achieve only 2-3 out of 10 on human realism ratings. To bridge algorithmic metrics with human perception, we further contribute WorldLens-26K, a 26,808-entry human-annotated preference dataset pairing numerical scores with textual rationales, and WorldLens-Agent, a vision-language evaluator distilled from these judgments that enables scalable, explainable auto-assessment. Together, the benchmark, dataset, and agent form a unified ecosystem for assessing generated worlds not merely by visual appeal, but by physical and behavioral fidelity.