StateCraft introduces a new architecture that separates a persistent, updatable abstract state from the visual state in video world models. By pairing a language model with a video diffusion model, it tracks entity changes over time and conditions visual generation on this abstract state. The approach is evaluated on generative interfaces and a new benchmark, showing improved generation quality, memory usage, and controllability, while enabling direct editing of unseen states and extending to spatial 3D environments.
By Lorenzo Venturoli, Nedko Savov, Xi Wang, Marc Pollefeys, Luc Van Gool
arXiv:2609.10540v1 Announce Type: new
Abstract: Recent video world models generate increasingly realistic and interactive visual experiences, yet lack reliable mechanisms for maintaining persistent w...
By Zheng-Hui Huang, Guixu Lin, Jiacheng Lin, Yi-Chuan Huang, Ruihan Yu, Muyao Niu, Siqi Yang, Yu-Lun Liu, Yung-Yu Chuang, Kaipeng Zhang, Zhixiang Wang
AgentGarten is a framework that links simulators and game engines with a shared neural renderer to create real‑time interactive virtual worlds. It uses a pretrained video model adapted to geometry conditions, refined with Adversarial Forcing, to produce realistic visual observations while maintaining consistent state and rules. The system enables agents to learn efficiently—achieving comparable performance in only four training rounds versus millions in traditional reinforcement learning—by distilling experience into playbooks that successive agents can inherit and improve upon.
By Jiawei Chi, Shangchen Miao, Zhiyuan Shi, Kailu Wu, Hanyang Wang, Weiliang Chen, Qiyu Dai, Jinshan Ren, Jun Gao, Mingsheng Long, Yueqi Duan, Jiangran Lyu, Jialong Wu, Fangfu Liu
WorldMind is a decoupled framework for state-aware NPC behavior in game world models, separating interactive world modeling into four layers: Understanding, Decision, Control, and Generation. It constructs a compact state from generated frames, reasons over it to plan NPC actions, translates actions into temporally aligned conditions, and synthesizes visual outcomes. Experiments on the newly introduced BOSS-140K dataset show that WorldMind achieves more tactically appropriate and coherent NPC behavior than baseline models in about 70% of pairwise comparisons.
By Zhiyang Deng, Boran Zhang, Danze Chen, Yeying Jin
Oneira is an interactive video world model that links open-ended generation with persistent interaction. It uses a coding agent to manage an extensible world state, allowing newly generated or discovered entities to become actionable and ensuring that changes made by an agent are retained across video segments. Experiments demonstrate that Oneira supports consistent interaction with new objects while preserving prior interaction effects over long horizons.
By Xindi Yang, Baolu Li, Liam Lee, Zhenfei Yin, Songxin Zhang, Zhuoyang Song, Xu Jia, Jianfei Cai, Tien-Tsin Wong, Bingyi Jing, Mengyue Yang
The paper introduces Code World Model, a framework that decouples world evolution from visual rendering by using a coding agent as a world brain. The agent reasons about events, generates executable code to maintain persistent state, and a proxy representation links this state to a video model for high‑fidelity visual output. Experiments with MiniMax‑H3 show that the system can follow proxy‑based spatiotemporal specifications while preserving rich visual dynamics, illustrating a new approach to open‑ended world modeling.
By Yiwen Chen, Guosheng Lin, Chi Zhang
arXiv:2608.24680v1 Announce Type: new
Abstract: Video games provide a scalable source of training data for video world models, offering diverse environments, complex interactions, and abundant in-the...
By Wenxuan Shen, Dongna Jin, Dongping Chen
arXiv:2609.25652v1 Announce Type: new
Abstract: Recent game world models support realistic visual simulation and interactive gameplay based on player inputs. However, they typically learn environment...
By Zijun Lin, Zhiyang Deng, Yuzhe Wu, Bihan Wen, Yeying Jin
arXiv:2605.13335v2 Announce Type: replace
Abstract: Embodied agents in household environments must plan under partial observation: they need to remember objects, track state changes, and recover when...
By Qinchuan Cheng, Zhantao Gong, Pengzhan Sun, Angela Yao, Xulei Yang, Shijie Li
arXiv:2607. 27380v2 Announce Type: replace-cross Abstract: Text-to-video models have achieved remarkable visual quality, yet they still struggle to generate physically consistent dynamics because the temporal evolution of a scene must be inferred implicitly from a highly compressed text prompt.
By Haodong Li, Tianfei Ren, Xiaoxiao Ma, Chunmei Qing, Zhen Fang, Sipeng He, Ziyu Guo, Haoyu Wu, Juanxi Tian, Yihang Zou, Ruichuan An, Dongzhi Jiang, Boxue Yang, Ji Xie, Xu Huang, Wenhao Yan, Jialv Zou, Zhengrong Yue, Yaxin Luo, Xiaotong Li, Yuzhu Wang, Junyan Ye, Jinjing Zhao, Zehui Chen, Lin Chen, Renye Yan, Feng Zhao, Pheng-Ann Heng
DeXplicit is a dexterous manipulation world model that explicitly predicts metric 3D object-centric motion and deformation before rendering visual outcomes. By separating 3D dynamics from visual synthesis, it provides a structured scaffold for video generation, enabling efficient causal generation with only two denoising steps per block. Experiments on HOT3D, OakInk2, and PhysTwin show significant reductions in moved-point error and improvements in object fidelity, while achieving a 57× speedup over a 14B bi-directional baseline.
By Adam Lee, Mutian Xu, Yukang Cao, Shulin Tian, Ziwei Liu
arXiv:2610.27999v1 Announce Type: new
Abstract: Moving from controllable videos to genuinely playable worlds requires persistent world state, executable game rules, and low-latency interaction. We ou...
By Jihai Zhang, Runjia Qian, Kaiqin Kong, Biao Jiang, Puyi Wang, Siru Chen, Tianle Li, Guanjie Chen, Junyi Wu, Chubin Chen, Yuanhang Li, Kaichen Huang, Haobo Zhang, Yangguang Li, Wei Yu, Guibin Chen, Yu Cheng, Yahui Zhou