Action-Conditioned World Models

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54 papers in the last four weeks, up 260% on the four weeks before. 0.5% of all new papers.

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Long-WAM: Scaling the Context of World-Action Models
Oct 7, 2026Wei Huang, Bohan Zhang, Chenzhi Liu +13Long-Horizon Robotic Manipulation Action-Conditioned World Models
NVIDIA · HKU · MIT +1
ΔWAM: Distilling Action Tangent Fields into World Action Models
Oct 7, 2026Ke Wu, Hanwen Huang, Bo Gu +6World Model Learning Action-Conditioned World Models
Fudan University · TARS Robotics · ShanghaiTech University +2
Kuration SDK: Addressing the Virtual2Real Gap via Data Curation
Oct 7, 2026Nirmit Desai, Eric Song, Mayank Sengupta +4Training Data Curation Action-Conditioned World Models
AIntropy AI
World Models Dream of Success: Diagnosing and Repairing Failure Insensitivity in Robot World Models
Oct 6, 2026Jiuyi Xu, Xiao Hu, Meida Chen +3World Models for Robotics Action-Conditioned World Models
Colorado School of Mines · Northeastern University · Institute for Creative Technologies, University of Southern California +1
RIWANav: Recursive World-Action Models with Self-Improvement for Urban Navigation
Oct 6, 2026Jing Xie, Shouwei Ruan, Yubin Wang +4Robot Policy Learning World Model Learning
MoE Key Lab of Artificial Intelligence, Institute of AI, School of Computer Science, Shanghai Jiao Tong University, Shanghai, China · Beihang University, Beijing, China · The Hong Kong University of Science and Technology, Hong Kong, China +3
Independent Multi-Agent Reinforcement Learning with Counterfactual Semantic-Social World Models
Oct 6, 2026Fernando Martinez, Tao Li, Yingdong Lu +1Sequential MARL Action-Conditioned World Models
Department of Computer and Information Sciences, Fordham University, New York, NY, 10023, USA · Department of Systems Engineering, City University of Hong Kong, Hong Kong SAR, 999077, China · IBM Research, Yorktown Heights, NY, 10598, USA
Long-Horizon Textual World Modeling through Structured Reasoning
Oct 5, 2026Fangxin Wang, Xiang Gao, Yuguang Yao +3World Models Action-Conditioned World Models
Intuit AI Research
Mind the Execution Gap: Action-Semantic Mismatch in World-Model Control
Oct 5, 2026Shengtao Wen, Xiang Chen, Yu Tian +3World Model-Based Planning Action-Conditioned World Models
Nanjing University of Aeronautics and Astronautics, Nanjing, China · Tsinghua University, Beijing, China · Nanjing University, Nanjing, China
KineWorld: Action-Induced Transport Fields for Embodied World Modeling
Oct 5, 2026Ziying Song, Yuchen Liu, Zhuoran Xu +6Action-Conditioned Video Generation Video Diffusion Models
Nanyang Technological University · North University of China · Psibot +4
When Low Prediction Error Misleads Planning: Diagnosing Representation, Dynamics, and Decision Failures in Latent World Models
Oct 4, 2026Rui Min, Xianyao Li, Fang Xu +1World Model-Based Planning Action-Conditioned World Models
Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL 32611, USA · Department of Civil and Coastal Engineering, University of Florida, Gainesville, FL 32611, USA
FLEX-WAM: Flexible Block-Causal World-Action Models for Long-Horizon Imagination and Planning
Oct 4, 2026R. Khorrambakht, Joseph Amigo, Félix Lebel +4World Model-Based Planning Action-Conditioned World Models
Center for Robotics and Embodied Intelligence (CREO), New York University · Courant Institute of Mathematical Sciences and Center for Data Science, New York University · Ecole normale supérieure - PSL +2
$R^2$ -WAM: Repair-and-Reject Post-Training for World Action Models
Oct 4, 2026Ruiyan Xu, Haisheng Su, Sixu Lin +4World Action Models Action-Conditioned World Models
The Chinese University of Hong Kong, Shenzhen · Manifold AI · Southeast University +1
On the Divergence of Accuracy and Mechanism Consistency in Time Series World Models
Oct 1, 2026Haochen Zhang, Jiaheng Guo, Zhen Xu +4World Models Time Series Forecasting
University of North Carolina at Chapel Hill · Foci Labs · Stevens Institute of Technology
Oneira: From Open-Ended Generation to Open-World Interaction in Video World Models
Oct 1, 2026Xindi Yang, Baolu Li, Liam Lee +8Long-Horizon Video Generation Action-Conditioned World Models
Monash University · Dalian University of Technology · The Chinese University of Hong Kong, Shenzhen +2
Completion Aware Guidance for World Action Models
Oct 1, 2026Seungyeon Kim, Junhoo Lee, Baekseung Kim +2World Models Action-Conditioned World Models
Seoul National University · KAIST
Network World Models as Environments for Algorithm Design on Complex Systems
Oct 1, 2026Rishab Alagharu, Hongji Pu, Zeeshan Memon +3Automated Algorithm Discovery World Model-Based Planning
Emory University · University of Illinois Urbana-Champaign
CtrlWAM: Controllable World Action Models with Aligned Intent and Foresight
Oct 1, 2026Chensheng Peng, Wenhao Ding, Ran Tian +9World Models for Robotics Action-Conditioned World Models
NVIDIA · UC Berkeley · UCLA
JEPA-TTT: Persistent Test-Time Training of Latent World Models for Planning under Dynamics Shifts
Sep 30, 2026Zheyuan Zhang, Suyu Ye, Nakul Agarwal +5Test-Time Adaptation Latent Dynamics Modeling
Honda Research Institute USA · Johns Hopkins University
Token-World: World Modeling in Vision-Language Model Token Space for Robot Manipulation
Sep 30, 2026Chuyao Fu, Xiaowei Chi, Yuhan Rui +14World Models Action-Conditioned World Models
Southern University of Science and Technology · MUKA Robotics · Hong Kong University of Science and Technology +3
Learning Skills from Historical Action Trajectories: Action Experience Dictionary for World Action Models
Sep 30, 2026Qi Lyu, Jiahua Dong, Hao Shen +9Robot Skill Learning Action-Conditioned World Models
Shenyang Institute of Automation, Chinese Academy of Sciences · Mohamed bin Zayed University of Artificial Intelligence · Anhui University +3
DashVMC: Real-Time Discrete World Model Control in Geometry Dash
Sep 30, 2026Florent Tariolle, Florian YgerAction-Conditioned World Models Model-Based RL
INSA Rouen Normandy
Magic-W0: A Structured World-Action Foundation Model for Physical Intelligence
Sep 30, 2026Xuhua Chen, Zhenhan Yin, Yuan Zhang +15Robot Foundation Models Action-Conditioned World Models
Magic-Lab Team, Magiclab Robotics Inc.
ReWAM: Reciprocal World Action Models for Interactive Autonomous Driving
Sep 30, 2026Benshan Ma, Pei Liu, Ruiguo Zhong +4Action-Conditioned World Models Multi-Agent Systems
The Hong Kong University of Science and Technology (Guangzhou) · Leapmotor · The Hong Kong University of Science and Technology
The Planning Limits of Latent World Models
Sep 30, 2026Ali Alrasheed, Basim Azam, Naveed AkhtarWorld Model-Based Planning Action-Conditioned World Models
The University of Melbourne, Australia
Rethinking Representations for World-Action Modeling
Sep 29, 2026Haoyi Jiang, Liu Liu, Xinjiang Wang +12World Model Learning Action-Conditioned World Models
Huazhong University of Science & Technology · Horizon Robotics · Fudan University +2
CogWAM: Aligning Semantic Cognition with World Action Modeling via Event-Driven Interfaces
Sep 29, 2026Sen Wang, Liu Liu, Xinjiang Wang +7World Models for Robotics Language-Conditioned Robot Manipulation
Xi'an Jiaotong University · Horizon Robotics · Huazhong University of Science and Technology +1
Beyond a single latent space: a dual-latent world model for long-horizon planning
Sep 29, 2026Delin Zhao, Zhengrong Yue, Shaobin Zhuang +6World Model-Based Planning Action-Conditioned World Models
Nanjing University · Shenzhen University of Advanced Technology · Shanghai Jiao Tong University +1
Anisotropic Representations Improve Planning in JEPA World Models
Sep 29, 2026Mingu Kang, Yoori Oh, Sookyung Kim +1Representation Learning World Model-Based Planning
Seoul National University · Ewha Womans University
Direct Experience World-Model Optimization: Learning the World Beyond Action Imitation
Sep 29, 2026Xiangcheng Zhan, Zirui Chen, Yicheng Zhao +2Test-Time Adaptation World Model Learning
Harbin Institute of Technology · Dalian University of Technology · Southern University of Science and Technology
Do-JEPA: From Masking to Intervention in Latent World Models
Sep 29, 2026Hossein Resani, Javen Qinfeng ShiCausal Effect Estimation Causal World Models
Australian Institute for Machine Learning, Adelaide University · Responsible AI Research Centre

Oct 7, 2026, cs.ROJ/K move · Enter open · S save

Long-WAM: Scaling the Context of World-Action Models

Wei Huang, Bohan Zhang, Chenzhi Liu, Isabella Liu+12

NVIDIA · HKU · MIT+1

Long-Horizon Robotic Manipulation Action-Conditioned World Models Efficient Inference for World Action Models Video Prediction

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Real-time robot control demands enough visual history to infer motion and task progress, but processing that history can delay action. We present Long-WAM, a model-system framework for scaling the context of causal world-action models under real-time control constraints. Our central finding is that access to history is not the same as using it: longer histories pay off far more when the video foundation is pretrained autoregressively (AR). We first learn causal prediction from robot and egocentric videos without action labels, then preserve this history-to-future structure during world-action adaptation. On RoboCasa GR-1, increasing context from 0.0 to 19.2 seconds raises success from 63.3% to 78.7%, whereas a bidirectionally pretrained initialization shows no net gain; robot-domain AR pretraining further raises peak success on GR-1 and LIBERO-Long. Long-WAM also achieves the best results among compared methods on LIBERO-Long, RoboTwin 2.0, and DOMINO. Streaming observation encoding, asynchronous execution, and hardware-specific acceleration enable deployment on RTX 5090, DGX Spark, and Jetson AGX Thor without dropping future prediction; on RTX 5090, each action chunk, including future-video latent prediction, takes 107.4 ms. Real-time deployment on Unitree G1 and YAM supports dynamic and long-horizon manipulation, including 95% success on dynamic cup stacking, where Pi0.5 and Fast-WAM succeed in none of 20 trials. As a memory-informed executor, Long-WAM also complements higher-level planning in composite tasks.

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Latest papers 216