💡 The paper presents AlayaWorld, an interactive long-horizon video world model that generates interactive environments from user inputs instantly. Unlike conventional video game development, which relies on labor-intensive pipelines for asset production, animation, physics, and programming, video world models like AlayaWorld enable the creation of customized, explorable, and continuously evolving virtual worlds from text, image, or video.

To achieve this, AlayaWorld requires four tightly coupled capabilities: interaction, persistent spatiotemporal consistency, stable long-horizon generation, and efficient response. The model is built on a 15B video diffusion transformer and generates 24-fps video at 540p and 720p. It produces short latent chunks autoregressively under camera trajectories and switchable text prompts.

The model's bounded visual context combines a persistent sink frame, compressed temporal history, geometry-aligned spatial memory, and recent-frame conditioning. To reduce long-term drift, the model is trained with corrupted histories and prediction residuals collected from its own rollouts. The authors also introduce 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.

The results show that AlayaWorld achieves the best performance over long-horizon generation on the iWorld-Bench dataset. The model is conceived as a full-stack, open-source, and long-term project, intended to provide an extensible foundation for future research on interactive video world models. Overall, AlayaWorld's contributions include its ability to generate interactive and stable long-horizon video, its efficient response to user inputs, and its potential to enable the creation of complex and evolving virtual worlds.

💡 The paper introduces Alaya Renderer Flash, a real-time generative forward world renderer that significantly improves the speed of the original Alaya Renderer. The original Alaya Renderer was too computationally expensive for real-time deployment, running at only 0.56 frames per second. In contrast, Alaya Renderer Flash achieves 31.54 frames per second, making it suitable for interactive world modeling and user-controllable play.

The key contribution of Alaya Renderer Flash is its reformulation of the original renderer as a few-step autoregressive streaming model, which enables efficient latent encoding and frame reconstruction. This approach preserves the scene structure without altering the underlying world dynamics, unlike models that generate frames from text or control hints. Additionally, Alaya Renderer Flash retains the teacher model's G-buffer and text-prompt interfaces while enabling continuous rendering over input streams of unbounded length.

The authors evaluate Alaya Renderer Flash on G-buffer streams across various metrics, including content preservation, temporal consistency, cross-window stability, prompt controllability, and runtime efficiency. The results show that Alaya Renderer Flash substantially reduces inference cost while preserving the core rendering capabilities of the teacher model. By integrating Alaya Renderer Flash with a physics engine, the authors build a fully playable generative world running at 30 frames per second, demonstrating the potential of this approach for real-time interactive applications. Overall, Alaya Renderer Flash offers a promising alternative path towards interactive world modeling and user-controllable play.