Building interactive worlds that respond coherently to player actions has long been a shared goal of computer graphics, games, and artificial intelligence. Recent video generative models provide a data-driven route toward this goal by predicting future observations conditioned on user actions, and are increasingly regarded as potential next-generation game engines. Realizing a genuinely interactive game world, however, requires interaction outcomes that follow rules over evolving game conditions, consequences that persist over long horizons, and a generation loop that operates in real time. Conventional game engines realize these properties through a recurrent action-state-observation loop, in which player actions update an explicit game state according to predefined rules and observations are rendered from the resulting state. Taking this loop as an organizing lens, this paper examines interactive game world modeling along four dimensions: player action control, game state dynamics, state-observation persistence, and real-time interactive generation. For each dimension, we start from the capabilities required by an interactive game world, group existing approaches into representative families, and discuss the strengths and trade-offs of each family. Complementing this analysis, we present a scalable data engine for Black Myth: Wukong that collects over 90 hours of gameplay with frame-aligned player actions, ground-truth game states, and visual observations, together with structured and semantic annotations, as a resource for state-aware game world modeling. We hope this paper offers a clear picture of where the field stands and fosters progress toward interactive game worlds.
Zhen Li, Zian Meng, Shuwei Shi et al.· arXiv.org· 2 citations
The new version of AlayaWorld substantially revise how conditioning signals are represented and integrated into the model, replacing the previous depth-warping-based spatial memory with a streaming 3D point-cache renderer.
AlayaWorld Team Kaipeng Zhang, Chuanhao Li, Y. Zhan et al.· 1 citation· ⚡1
AlayaWorld enables open-ended real-time interaction, allowing users to freely navigate and perform diverse actions such as combat, spell casting, and monster summoning, and the framework unifies the complete development-from data preparation model architecture, model training, inference acceleration, and deployment-within a modular and extensible architecture.
AlayaWorld Team, Kaipeng Zhang, Chuanhao Li et al.· arXiv.org· 1 citation
Sekai2 is introduced, a multi-source real-world video dataset that carries the world-exploration footage of Sekai toward interactive world modeling, and Corpus-scale analyses demonstrate complete pose-and-caption coverage, broad geographic and semantic diversity, varied camera trajectories, and highly non-redundant temporal descriptions.
Kang He, Wenshuo Peng, Zihui Gao et al.· 1 citation
AlayaWorld is presented, an interactive long-horizon video world model that generates 24-fps video at 540p and 720p and introduces a discrete autoregressive distillation formulation that combines distribution-matching distillation, self-forcing++, and consistency distillation, reducing inference from approximately 30 sampling steps to four steps per chunk.
AlayaWorld Team Kaipeng Zhang, Chuanhao Li, Y. Zhan et al.· arXiv.org· 4 citations
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