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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SCOPE: Simulating Cross-game Operations in Playable Environments for FPS World Models
May 22, 2026Zizhao Tong, Yeying Jin, Hongfeng Lai +11Action-Conditioned Video Generation Video Diffusion Models
UCAS-Terminus AI Lab, University of Chinese Academy of Sciences · Tencent · National University of Singapore +6
WorldKV: Efficient World Memory with World Retrieval and Compression
May 21, 2026Jung Yi, Minjae Kim, Paul Hyunbin Cho +3KV Caching Memory-Augmented Video Generation
1KAIST AI · 2Naver AI Lab
ChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data
May 21, 2026Jiangyuan Wang, Xuyong Chen, Junwei He +3Latent Dynamics Modeling Healthcare
Beijing KidneyTec Medical Technology Co., Ltd., Beijing, China
Incantation: Natural Language as the Action Interface for Multi-Entity Video World Models
May 18, 2026Shangwen Zhu, Qianyu Peng, Zhao Pu +12Action-Conditioned Video Generation Long-Horizon Video Generation
1SJTU · 8HKU · 3Matrix Team +6
WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform
May 18, 2026Yu Shang, Yinzhou Tang, Yiding Ma +22World Models for Robotics World Models
Tsinghua University · Shanghai Jiao Tong University · Zhejiang University +7
DiLA: Disentangled Latent Action World Models
May 15, 2026Tianqiu Zhang, Muyang Lyu, Yufan Zhang +2Action-Conditioned Video Generation Latent Action Learning
Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, IDG/McGovern Institute for Brain Research, Peking University. · Center of Quantitative Biology, Peking University. · School of Psychological and Cognitive Sciences, Key Laboratory of Machine Perception (Ministry of Education), Peking 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
SCAR: Self-Supervised Continuous Action Representation Learning
May 13, 2026Hongjia Liu, Fan Feng, Minghao Fu +3Latent Action Learning Representation Learning
University of California, San Diego · KTH Royal Institute of Technology
HarmoWAM: Harmonizing Generalizable and Precise Manipulation via Adaptive World Action Models
May 11, 2026Qiuxuan Feng, Jiale Yu, Jiaming Liu +8World Models for Robotics Action-Conditioned World Models
State Key Laboratory of Multimedia Information Processing, School of Computer Science, Peking University · The Chinese University of Hong Kong · Simplexity Robotics
PROWL: Prioritized Regret-Driven Optimization for World Model Learning
May 11, 2026Ahmet H. Güzel, Jenny Seidenschwarz, Benjamin Graham +3Adversarial Training World Model Learning
University College London AI Centre · Odyssey · University of Basel
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
One Token Per Frame: Reconsidering Visual Bandwidth in World Models for VLA Policy
May 8, 2026Zuojin Tang, Shengchao Yuan, Xiaoxin Bai +4Action-Conditioned World Models Efficient VLA Models
Zhejiang University · Central South University · Harbin Institute of Technology +2
NoiseGate: Learning Per-Latent Timestep Schedules as Information Gating in World Action Models
May 8, 2026Wen Huang, Haoran Sun, Yongjian Guo +8Action-Conditioned Video Generation Action-Conditioned World Models
Tsinghua University · Peking University · JDT AI Infra +1
Learning Visual Feature-Based World Models via Residual Latent Action
May 8, 2026Xinyu Zhang, Zhengtong Xu, Yutian Tao +3Latent Action Learning World Model Learning
Rutgers University · Purdue University · University of Wisconsin-Madison
OA-WAM: Object-Addressable World Action Model for Robust Robot Manipulation
May 7, 2026Yushan Liu, Peibo Sun, Shoujie Li +7World Models for Robotics Action-Conditioned World Models
Tsinghua University · Shanghai Jiao Tong University · Nanyang Technological 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
When to Trust Imagination: Adaptive Action Execution for World Action Models
May 7, 2026Rui Wang, Yue Zhang, Canyang Chen +3Long-Horizon Robotic Manipulation World Models for Robotics
Southern University of Science and Technology, Shenzhen, China · The University of Hong Kong, Hong Kong, China
EA-WM: Event-Aware Generative World Model with Structured Kinematic-to-Visual Action Fields
May 7, 2026Zhaoyang Yang, Yurun Jin, Lizhe Qi +2Action-Conditioned Video Generation Video Diffusion Models
Fudan University · Zhongguancun Institute of Artificial Intelligence · University of Science and Technology of China +2
Motubrain: An Advanced World Action Model for Robot Control
Apr 30, 2026Motubrain Team, Chendong Xiang, Fan Bao +17Robotic Control World Models for Robotics
Motubrain Team
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
Privileged Foresight Distillation: Zero-Cost Future Correction for World Action Models
Apr 28, 2026Pengcheng Fang, Hongli Chen, Xiaohao CaiWorld Model Learning Action-Conditioned World Models
The University of Southampton · The University of Queensland
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
Beyond Patient Invariance: Learning Cardiac Dynamics via Action-Conditioned JEPAs
Apr 24, 2026Jose Geraldo Fernandes, Luiz Facury, Pedro Robles Dutenhefner +1Latent Dynamics Modeling Healthcare
Department of Computer Science Universidade Federal de Minas Gerais Belo Horizonte, Brazil
Hi-WM: Human-in-the-World-Model for Scalable Robot Post-Training
Apr 23, 2026Yaxuan Li, Zhongyi Zhou, Yefei Chen +5Robot Policy Learning Robot Policy Adaptation
Current Robotics · Tsinghua University · Peking University +1
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
MultiWorld: Scalable Multi-Agent Multi-View Video World Models
Apr 20, 2026Haoyu Wu, Jiwen Yu, Yingtian Zou +1Multi-View Consistency Action-Conditioned World Models
The University of Hong Kong · Sreal AI
Active World-Model with 4D-informed Retrieval for Exploration and Awareness
Apr 17, 2026Elaheh Vaezpour, Amirhosein Javadi, Tara JavidiActive Perception World Model Learning
KavAI · UCSD
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
RAE-NWM: Navigation World Model in Dense Visual Representation Space
Mar 10, 2026Mingkun Zhang, Wangtian Shen, Fan Zhang +3Visual Navigation World Model Learning
Department of Precision Instrument, Tsinghua University, Beijing, China · University of Rochester, Rochester, NY, USA · Beijing Information Science and Technology University, Beijing, China

May 22, 2026, cs.CVJ/K move · Enter open · S save

SCOPE: Simulating Cross-game Operations in Playable Environments for FPS World Models

Zizhao Tong, Yeying Jin, Hongfeng Lai, Zeqing Wang+10

UCAS-Terminus AI Lab, University of Chinese Academy of Sciences · Tencent · National University of Singapore+6

Action-Conditioned Video Generation Video Diffusion Models Action-Conditioned World Models Interactive World Models

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Interactive world models for first-person shooter (FPS) games must resolve high-frequency overlapping control signals at every frame without disrupting unaffected regions. Existing methods inject actions globally and train on single titles, failing under dense FPS inputs. We observe that FPS actions are spatially selective: discrete events such as firing or reloading affect only a localized region around the weapon (the scope), while continuous camera and movement signals govern stable surroundings. We propose SCOPE, which inserts a conditioning module into each transformer block of a pretrained video diffusion model. It reshapes features into per-pixel temporal sequences so that each position computes its action response from local visual content. This separates in-scope effects from out-of-scope generation without segmentation labels. We also introduce CrossFPS, the first multi-game FPS dataset with frame-aligned action telemetry. It comprises 69K clips from 7 titles with 10-DoF controller signals, curated to remove gameplay bias. The model learns general visual-to-action mappings rather than game-specific patterns, enabling zero-shot transfer to unseen scenes. Experiments confirm strong action responsiveness, precise scope separation, and effective cross-game generalization.

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