Action-Conditioned World Models

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From Prediction to Decision: World-Model-Guided Action Selection for Continuous Pile Excavation
Sep 14, 2026Ailing Zhang, Fan Gao, Song Zhang +3World Models for Robotics Action-Conditioned World Models
1Tsing-AI (Shanghai) Technology Co., Ltd. · 2Shanghai Jiao Tong University. · 3Shanghai Ocean University.
Reconstructing Is Not Acting: Action-Centric Latent Dynamics Modeling
Sep 14, 2026Dingjie Fu, Dianxing Shi, Yangyang Xu +1Latent Action Learning Latent Dynamics Modeling
Harbin Institute of Technology (Shenzhen) · Beihang University
Pelican-Sim 1.0: A General World Model Simulator for Embodied Intelligence
Sep 14, 2026Shilong Zou, Shilin Zhang, Yingji Zhang +8World Models Action-Conditioned World Models
Beijing Innovation Center of Humanoid Robotics (X-Humanoid) WFM System Group
IMPLY: Physically Anchored Consistency for World-Model Rollouts
Sep 14, 2026Aman Mehta, Riya BaviskarWorld Models Action-Conditioned World Models
Independent Researcher
World Models for Cross-Machine CNC Transfer under Partial Sensor Overlap
Sep 13, 2026Ayoub Louaye Bouaziz, Matthieu Ostertag, Anton DemaslesManufacturing World Model Learning
Université de Bretagne Occidentale, Brest, France · Mines Nancy, Université de Lorraine, Nancy, France
Valerant: An Automatic Navigable Game Map Generator via Action-Conditioned World Model Exploration
Sep 8, 2026Yiran Qiao, Feng Wang, Jing MaWorld Model-Based Planning Action-Conditioned World Models
Case Western Reserve University · Johns Hopkins University
SyncWorld: Visual Calibration Enables World Models as Zero-Shot Simulators
Sep 8, 2026Yuncong Yang, Zhengtao Han, Furkan Ozyurt +6World Model Learning World Models for Robotics
UMass Amherst · UC Berkeley · NYU +1
Earth System World Model for What-If Simulations: A Case Study for Terrestrial Ecosystems
Sep 8, 2026Zhihao Wang, Ruichen Wang, Ruohan Li +6Surrogate Modeling World Model Learning
University of Maryland · Rutgers University · University of Texas at Austin +1
WorldAgen: Unified State-Action Prediction with Test-Time World Model Training
Sep 8, 2026Chi Wan, Kangrui Wang, Yuan Si +2Test-Time Adaptation Action-Conditioned World Models
Northwestern University
CST-WM: A Causally Structured World Model for Embodied Visual Tracking
Sep 5, 2026Junyi Hu, Shuaihang Yuan, Jiazhao Liang +1Causal World Models Visual Object Tracking
New York University Abu Dhabi
Toward Physically Grounded JEPA World Models for Goal-Conditioned Robotic Planning
Sep 3, 2026Muyuan Liu, Yue Huang, Zheng Liang +1World Models for Robotics World Model-Based Planning
GENISOM AI, Beijing, China
GPU-Accelerated Astrodynamics World Models for Spacecraft Rendezvous and Proximity Operations
Sep 2, 2026Duncan Eddy, Isaac R. Ward, Grace Ra Kim +1Spacecraft Rendezvous and Proximity Operations World Models
Stanford University
AGI Maze Prediction Datasets: A Compact Benchmark for Learning World Dynamics with Transformers
Sep 2, 2026Alexey PotapovWorld Models Action-Conditioned World Models
SingularityNET Foundation
Belief-Calibrated Optimization: An Explicit World Model for Agentic Optimization
Sep 1, 2026Yuhan Chen, Zhihua Tian, Mahavir Dabas +7Large Language Model-Guided Optimization Action-Conditioned World Models
1Virginia Tech · 2Amazon · 3Independent Researcher
IMPACT: Attention Is the Interaction Map for Scalable Interaction-Aware World Model Training
Aug 31, 2026Rongze Tang, Jianjie Fang, Zhaolu Wang +8World Model Learning Action-Conditioned World Models
University of Science and Technology of China · 2Zhongguancun Academy · 3Tsinghua University +1
CAER: Causal Action Effect Reweighting for World Model Training
Aug 31, 2026Jianjie Fang, Xvyuan Liu, Ziyou Wang +9Action-Conditioned Video Generation World Model Learning
1Tsinghua University · University of Science and Technology of China · 2Manifold AI
Can Video World Models Track Unobserved World States?
Aug 31, 2026Joonghyuk Shin, Yicong Hong, Jaesik Park +1Action-Conditioned World Models Length Generalization
Seoul National University · Roblox
Hydra: A Navigation World Action Model with Discrete Latent Planning and Continuous Flow-Matching Execution
Aug 29, 2026Mohammad Nazeri, Alexandyr Card, Samira Huber +6Kinodynamic Motion Planning World Models for Robotics
George Mason University · Kiel University · Ludwig Maximilian University Munich +1
BehaviorWorldGen: Closing the Loop between Action Models and World Simulators via Controllable Behavior-Aware Structured World Generation
Aug 23, 2026Jiaqi Wang, Zhuo Zhang, Haining Guan +15Action-Conditioned World Models World Models for Autonomous Driving
AFARI World Model Team
ContactGuard: Pre-Contact Execution Monitoring with Action-Conditioned Latent World Models
Aug 13, 2026Gehan Zheng, Matthew Johnson-Roberson, Weiming ZhiRobot Failure Detection Contact-Rich Robotic Manipulation
College of Connected Computing, Vanderbilt University, USA. · School of Computer Science, The University of Sydney, Australia. · 3Australian Centre for Robotics, The University of Sydney, Australia.
Diagnosing JEPA World Models with Action-Conditioned Predictive Consistency
Aug 13, 2026Guo An, Zijing Wu, Honghua Dong +7World Models Joint-Embedding Predictive Architecture
Huawei · University of Science and Technology of China · Zhejiang University +3
FACT: Failure-Aware Causal Training for World-Action Models
Aug 10, 2026Quanquan Peng, Yutong Liang, Rui Yan +2Causal World Models Action-Conditioned World Models
University of California San Diego
Rethink Before You Execute: Adaptive Execution for World Action Models
Aug 10, 2026Feng Ye, Yiming Zhao, Yong Yu +5World Models for Robotics LLM Planning
Wangxuan Institute of Computer Technology, Peking University · Simplexity Robotics
WorldSimProbe: Diagnosing Simulator Faithfulness in Action-Conditioned World Models for Embodied Manipulation
Aug 10, 2026Peterson Co, Sicheng Hu, Chunxuan Jiao +17Robotics Simulation Action-Conditioned World Models
State Key Laboratory of Multimedia Information Processing, School of Computer Science, Peking University
4D-WAM: Infusing Spatiotemporal Awareness into World Action Models through Trajectory Fields
Aug 8, 2026Lishan Yang, Wenxuan Song, Xi Wang +14World Models for Robotics Action-Conditioned World Models
Adelaide University · HKUST(GZ) · Tsinghua University +3
CausalNav: Reliability-Certified Causal World Models for Control under Physical-Parameter Shift
Aug 7, 2026Yiyao Zhang, Diksha Goel, Hussain Ahmad +2Causal World Models World Models
School of Computing and Information Technology, University of Wollongong, Wollongong, NSW, Australia · CSIRO’s Data61, Clayton, VIC, Australia · School of Computer Science and Information Technology, Adelaide University, Adelaide, SA, Australia
SpikeWorld: Fast-State Adaptation for Frozen Spiking World Models
Aug 7, 2026Ziqiao YuTest-Time Adaptation World Model Learning
DiDi International Business Group
Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction
Aug 7, 2026Xinyi Li, Zaishuo Xia, Chenjie Hao +1World Model Learning Action-Conditioned World Models
University of California, Davis
Is Forward Prediction Enough? Physical State Grounding for JEPA World Models
Aug 7, 2026Haodong Yan, Jiaguan Zhu, Mingyuan Jia +12Physical Reasoning World Models for Robotics
1The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China · 2COCO Matrix
Dueling World Models: Advantage-Style Action Channels for Common-Mode Distractor Rejection
Aug 7, 2026Jiazhuo Li, Yiming Fei, Zhiruo Zhou +1Action-Conditioned World Models Latent World Models
University of Michigan, Ann Arbor, MI, USA · Zhejiang University, Hangzhou, China · Wuhan University of Technology, Wuhan, China +1

Sep 14, 2026, cs.ROJ/K move · Enter open · S save

From Prediction to Decision: World-Model-Guided Action Selection for Continuous Pile Excavation

Ailing Zhang, Fan Gao, Song Zhang, Kawa Leong+2

1Tsing-AI (Shanghai) Technology Co., Ltd. · 2Shanghai Jiao Tong University. · 3Shanghai Ocean University.

World Models for Robotics Action-Conditioned World Models Robotics Model-Based Planning

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Wheel-loader excavation is a sequential decision problem in which every scoop changes the terrain available to subsequent actions. A practical world model must predict action consequences accurately, rank candidates in real time, and operate inside the closed loop of a full-size machine. We present the World-Action Model (WAM), which proposes multiple scoops, rejects geometrically inadmissible candidates, jointly predicts signed terrain change and loaded volume, executes the candidate with the largest predicted load, and replans from the newly observed terrain. On 32 geometry-disjoint MinSlope test episodes, adding world-model ranking to matched diffusion proposals reduces the mean scoop count from 651.8 to 540.6 (17.1%), preserves 32/32 completion, and improves every paired episode. In a complete-system comparison, WAM completes 32/32 episodes versus 29/32 for an independently trained soft actor-critic policy. Comparisons of input representations, spatial support, and five architectures identify an accurate and efficient physics-structured predictor. We further evaluate the interface on event-disjoint full-size-loader data and deploy the complete perception-proposal-prediction-selection-execution loop for autonomous excavation. The ROS2/TensorRT implementation processes five candidates in 72.4 ms on a Jetson AGX Orin. The simulation results establish decision-level gains, while the physical experiments demonstrate real-world closed-loop feasibility.

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