World Models

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Generalization of World Models under Environmental Variability for Vision-based Quadrotor Navigation
Jun 3, 2026Luca Zanatta, Grzegorz Malczyk, Kostas AlexisWorld Models Scalable Robot Learning
Flash-WAM: Modality-Aware Distillation for World Action Models
Jun 3, 2026Arman Akbari, Ci Zhang, Arash Akbari +6Efficient World-Action Model
WAM-Nav: Asymmetric Latent World-Action Modeling for Unified Visual Navigation
Jun 3, 2026Ning Yang, Yan Huang, Kaiwen Peng +9Object Goal Navigation Menu
MAD: Mapping-Aware World Models for Agile Quadrotor Flight
Jun 3, 2026Xinhong Zhang, Runqing Wang, Yunfan Ren +6Quadrotor Flight 3D Mapping
OSCAR: Omni-Embodiment Action-Conditioned World Model for Robotics
Jun 3, 2026Zhuoyuan Wu, Jun GaoEfficient World-Action Model Robot Policies
CLAW: Learning Continuous Latent Action World Models via Adversarial Latent Regularization
Jun 2, 2026Tewodros Ayalew, Matthew Jeung, Samuel Wheeler +5Latent Actions Latent World Models
A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners
Jun 2, 2026Patrick Emami, Nan Qiang, Peter GrafLarge Language Model Planning Latent World Models
A 3D Isovist World Model -- Revealing a City's Unseen Geometry and Its Emergent Cross-City Signature
Jun 2, 2026Xuhui Lin, Stephen Law, Nanjiang Chen +23D Environments 3D World
World Models Meet Language Models: On the Complementarity of Concrete and Abstract Reasoning
Jun 2, 2026Yucheng Zhou, Wei Tao, Yiwen Guo +1World Models On-Policy
See Better, Foresee Better, Act Wiser: Physically Grounded Proactive Modeling and Decision Making
Jun 2, 2026Honghui Zhang, Anna Min, Chenmeinian Guo +9Multimodal Agents Agentic Commerce
AirDreamer: Generalist Drone Navigation with World Models
Jun 2, 2026Zian Liu, Andong Yang, Chunkai Yang +3Autonomous Drone Navigation Drone
GeoSem-WAM: Geometry- and Semantic-Aware World Action Models
Jun 2, 2026Fulong Ma, Daojie Peng, Wenjun Yue +4Efficient World-Action Model World Models
NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation
Jun 2, 2026NVIDIA, :, Aarti Basant +32Autonomous Driving Simulation Autonomous Driving
Cosmos 3: Omnimodal World Models for Physical AI
Jun 1, 2026NVIDIA, :, Aditi +293World Models Intelligence
MetaWorld: Scaling Multi-Agent Video World Model from Single-view Video Data
Jun 1, 2026Teng Hu, Mingchun Lu, Yating Wang +6Video World Models Monocular Videos
RoboDream: Compositional World Models for Scalable Robot Data Synthesis
Jun 1, 2026Junjie Ye, Rong Xue, Basile Van Hoorick +6Scalable Robot Data Synthesis Scalable Robot Learning
From Zero to Hero: Training-Free Custom Concept Spawning in World Models
Jun 1, 2026Kiymet Akdemir, Pinar YanardagWorld Models Autoregressive Model
Intercepting the Future: Latent-Space Predictive World Model for Dynamic VLA Manipulation
Jun 1, 2026Shahram Najam Syed, Arthur Jakobsson, Haoran Hao +1Vision-Language-Action Models Future Video Prediction
Geometry-Aware Implicit Memory for Video World Models
Jun 1, 2026Zhengxuan Wei, Xu Guo, Xinghui Li +8Video World Models Geometry-Aware Foundation Model
Policy and World Modeling Co-Training for Language Agents
Jun 1, 2026Ning Lu, Baijiong Lin, Shengcai Liu +9Agentic Reinforcement-Learning Framework World Models
CoMAP: Co-Evolving World Models and Agent Policies for LLM Agents
Jun 1, 2026Youwei Liu, Jian Wang, Hanlin Wang +1Large Language Model Agents Self-Evolving Agents
World-Task Factorization for Robot Learning
Jun 1, 2026Eduardo Sebastián, Adrian Pfisterer, Vito Mengers +2Robotics World Models
WALL-WM: Carving World Action Modeling at the Event Joints
Jun 1, 2026Shalfun Li, Victor Yao, Charles Yang +28Efficient World-Action Model Faster-Wam
Learning Action-Conditional and Object-Centric Gaussian Splatting World Models for Rigid Objects
Jun 1, 2026Jens U. Kreber, Lukas Mack, Joerg StuecklerEfficient World-Action Model World Models
Unified Driving Tokens: Representation- and Geometry-Guided Discrete Tokenizer for Driving World Models and Planning
Jun 1, 2026Ziyang Yao, Zeyu Zhu, YunCheng Jiang +2Autonomous Driving Visual Tokens
RA-LWLM: Retrieval-Augmented In-Context Localization with Wireless Foundation Models
Jun 1, 2026Guangjin Pan, Hui Chen, Hei Victor Cheng +1Wireless Networks Robust Localization
IMWM: Intuition Models Complement World Models for Latent Planning
Jun 1, 2026Baoqi Gao, Ruize Han, Miao Wang +1Latent World Models World Models
RoboTrustBench: Benchmarking the Trustworthiness of Video World Models for Robotic Manipulation
Jun 1, 2026Huiqiong Li, Jiayu Wang, Zhiting Mei +3Video World Models Counterfactual Reasoning
BRo-JEPA: Learning Modular Arithmetic in Latent Space
May 31, 2026Divyansh Jha, Yuanfang Xie, Varan Mehra +1Modular Addition Latent World Models
ImagineUAV: Aerial Vision-Language Navigation via World-Action Modeling and Kinodynamic Planning
May 31, 2026Xuchen Liu, Jiawei Huang, Shihao Xia +3Aerial Vision-Language Navigation Autonomous Drone Navigation
Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends
May 31, 2026Jiuming Liu, Chaojun Ni, Mengmeng Liu +7Video World Models World Models
Beyond Task Success: Behavioral and Representational Diagnostics for WAM and VLA
May 31, 2026Hung Mai, Bin Zhu, Tuan DoVision-Language-Action Models World Models
$τ_0$ -WM: A Unified Video-Action World Model for Robotic Manipulation
May 31, 2026Pengfei Zhou, Shengcong Chen, Di Chen +17Efficient World-Action Model Video World Models
MBench: A Comprehensive Benchmark on Memory Capability for Video World Models
May 30, 2026Shengjun Zhang, Zhang Zhang, Simin Huang +11Video World Models Longvideobench
SKIP: Sparse Keyframe Interpolation Paradigm for Efficient Embodied World Models
May 30, 2026Ziheng He, Yixiang Chen, Ning Yang +11Keyframe Selection World Models
V-LynX: Token Interface Alignment for Video+X LLMs
May 30, 2026Jungin Park, Jiyoung Lee, Kwanghoon SohnVisual Tokens Modality-Specific Encoders
Physical Object Understanding with a Physically Controllable World Model
May 30, 2026Rahul Venkatesh, Klemen Kotar, Lilian Naing Chen +9Video World Models World Models
StressDream: Steering Video World Models for Robust Policy Evaluation and Improvement
May 29, 2026Junwon Seo, Sushant Veer, Ran Tian +6Video World Models Dream
Dreaming Of Others: Latent Teammate Modeling In World Models For Multi-Agent Reinforcement Learning
May 29, 2026Tomas Leroy-StoneMulti-Agent Reinforcement Learning Latent World Models
AR Forcing: Towards Long-Horizon Robot Navigation World Model
May 29, 2026Yifei Yang, Zehua Fan, Huan Li +9Autoregressive Model Long-Horizon Planning
Light Interaction: Training-Free Inference Acceleration for Interactive Video World Models
May 29, 2026Jiacheng Lu, Haoyi Zhu, Sipei Yi +3Video World Models Training-Free Inference Framework
Subspace-Decomposed JEPAs: Disentangling Progression and Content in Latent World Models
May 29, 2026Lucas Thil, Jesse Read, Rim Kaddah +1Joint-Embedding Predictive Architectures Latent Bridge Matching
PatchWorld: Gradient-Free Optimization of Executable World Models
May 29, 2026Jiaxin Bai, Yue Guo, Yifei Dong +13World Models Markov Decision Processes
World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications
May 28, 2026Arif Hassan Zidan, Yi Pan, Hanqi Jiang +23World Models Artificial Intelligence Models
Physically Viable World Models: A Case for Query-Conditioned Embodied AI
May 28, 2026Adam J. Thorpe, Stepan Tretiakov, Cheng-Hsi Hsiao +6World Models Intelligence
YoCausal: How Far is Video Generation from World Model? A Causality Perspective
May 28, 2026You-Zhe Xie, Yu-Hsuan Li, Jie-Ying Lee +3Causal Reasoning World Models
minWM: A Full-Stack Open-Source Framework for Real-Time Interactive Video World Models
May 28, 2026Min Zhao, Hongzhou Zhu, Bokai Yan +9Video World Models Real-Time Systems
Toward AI That Understands Self and Others: A World-Model Theory of Cognitive Diversity and Alignment
May 28, 2026Toru TakahashiArtificial Intelligence Alignment Disagreement
World Models in Words: Auditing Physical State-Transition Commitments in Vision-Language Models
May 28, 2026Emmanuelle BourigaultWorld Models Scenario Generation
MiraBench: Evaluating Action-Conditioned Reliability in Robotic World Models
May 28, 2026Tianzhuo Yang, Zihan Shen, Zirui Mi +7Efficient World-Action Model E3Vs-Bench
Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players
May 27, 2026Fangfu Liu, Kai He, Tianchang Shen +7Video World Models World Models
DriveWAM: Video Generative Priors Enable Scalable World-Action Modeling for Autonomous Driving
May 27, 2026Chen Shi, Jinrui Xu, Shaoshuai Shi +3Video Pretraining Efficient World-Action Model
Hybrid Neural World Models
May 27, 2026Pranav Lakshmanan, Paras ChopraSurrogate Models Physical Dynamics
Do LLMs Build World Models From Text? A Multilingual Diagnostic of Spatial Reasoning
May 27, 2026Zhikai Pan, Chih-Ting Liao, Chunrui Liu +5Large Language Model Performance Spatial Reasoning
World Models for Robotic Manipulation: A Survey
May 27, 2026Fangyuan Wang, Ziyuan Wang, Guorui Pei +15World Models Scalable Robot Learning
SANTS: A State-Adaptive Scheduler for World Action Models
May 27, 2026Yirui Sun, Guangyu Zhuge, Keliang Liu +4Efficient World-Action Model World Models
Latent Goal Prediction from Language for Model-Based Planning
May 26, 2026Samuel Barbeau, Simon Roy, Giovanni Beltrame +2Classical Planning Latent World Models
What-If World: A Causal Benchmark for General World Models in Embodied Scenarios
May 26, 2026Kunlin Cai, Rui Song, Jinghuai Zhang +7Video World Models World Models
Riding the Shifting Potential: When Reactive Control Suffices for Multi-Goal Behavior
May 26, 2026Vito Mengers, Oliver BrockObstacle Avoidance Reactive
When Does LeJEPA Learn a World Model?
May 25, 2026David Klindt, Yann LeCun, Randall BalestrieroLatent World Models World Models

Jun 3, 2026 · cs.ROJ/K move · Enter open · S save

Generalization of World Models under Environmental Variability for Vision-based Quadrotor Navigation

Luca Zanatta, Grzegorz Malczyk, Kostas Alexis

Norwegian University of Science and Technology

World models, learned generative models that predict how an environment evolves, have become a promising tool for sample-efficient robot learning. Yet how robust they are to environmental variability remains poorly understood. To address this, we conduct a systematic study using vision-based quadrotor navigation as a testbed problem, training DreamerV3-based world models under varying levels of environmental randomness and evaluating them across all levels through cross-environment validation, spanning both Self-Supervised Learning (SSL) pretraining and Reinforcement Learning (RL) fine-tuning. We then deploy all world models and associated navigation policies on a real quadrotor in unseen environments, including an open-loop run where the model receives just 2.5s of real sensory input before all sensors are cut off, leaving the system to navigate entirely in imagination over a 12m traverse. Our results show that world model robustness during SSL pretraining is a strong predictor of sim-to-real transfer: every model that generalized well in cross-environment SSL validation deployed successfully in the real world, passing through gaps as narrow as 0.67m, whereas the model that dominated simulation policy evaluation failed on the real platform. We further identify (a) the discrete latent size and (b) the training-sequence length as the dominant factors governing world model quality.

World Models Scalable Robot Learning Quadrotor Flight Unknown Environments Environmental Uncertainty

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