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
GameWAM is the first World-Action Model designed for native closed-loop gameplay and GUI control in modern video games. It jointly generates future visual observations and executable keyboard-mouse trajectories using parallel visual and action generative processes, block-causal conditioning, and flow matching. The model predicts gameplay/GUI mode at each step, handles heterogeneous native controls, and employs block-cycle control for long-horizon interaction, achieving competitive task success with fewer native actions than prior agents.
By Yuncheng Guo, Zhanqiu Zhang, Yiwen Guo, Weijia Li
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
WorldGuide is a closed‑loop video world model that, given an initial image and a task goal, predicts an atomic action, generates the corresponding video clip, and uses that clip to decide the next action or terminate the task. It trains a Planner to predict the next action or completion from visual progress and an Executor to realize those actions, while a hierarchical visual memory tracks state over long horizons. The authors introduce WorldGuide‑Bench, a dataset of ~59K step‑annotated videos across 245 tasks, and show that WorldGuide outperforms the recent MiniMax‑H3 model on both WorldGuide‑Bench and VideoCraft‑Bench, highlighting the benefit of coupling planning with learned execution for goal‑directed procedural video generation.
By Ankan Deria, Komal Kumar, Hisham Cholakkal, Fahad Shahbaz Khan, Salman Khan
arXiv:2511.09057v4 Announce Type: replace-cross
Abstract: A world model is a cognitive simulator of the real-world environment allowing biological agents to reason about how the world evolves, whethe...
By PAN Team, Zihan Liu, Yi Gu, Mingkai Deng, Guangyi Liu, Zeyu Feng, Qiyue Gao, Yiyan Hu, Benhao Huang, Yichi Yang, Kun Zhou, Jiannan Xiang, Zhiting Hu, Zhengzhong Liu, Eric P. Xing
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