发表机构
Alaya Lab; University of California, Merced（阿莱雅实验室; 加州大学默塞德分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究如何提升生成式世界渲染器AlayaRenderer的速度，核心方法是将其重构为自回归流模型并引入轻量级编解码器，主要贡献是大幅降低推理成本，实现30 FPS可玩的生成式世界，保留核心渲染能力。
AI 中文摘要
生成式世界渲染器AlayaRenderer接收物理引擎导出的结构化世界状态并合成RGB帧。与从文本/控制提示生成帧的模型不同，它保留场景结构且不改变底层世界动态。然而，原始版本计算成本高。本技术报告介绍AlayaRenderer-Flash，将其帧率从0.56提升到31.54，达到游戏速度。它重新构建为自回归流模型并引入轻量级编解码器，保留教师模型的G缓冲区和文本提示接口，在多方面评估效果良好，集成后可构建30 FPS的可玩生成式世界。
英文摘要
Generative world renderer AlayaRenderer receives structured world states exported from physics engines and synthesizes RGB frames. Unlike models that generate frames from text/control-hints prompts, AlayaRenderer preserves scene structure without altering the underlying world dynamics. This demonstrates an alternative path toward interactive world modeling and user-controllable play. However, the original AlayaRenderer is too computationally expensive for real-time deployment. This technical report introduces AlayaRenderer-Flash, a real-time-oriented generative forward world renderer that pushes AlayaRenderer from 0.56 FPS to 31.54 FPS, reaching the speed of play. AlayaRenderer-Flash reformulates the original renderer as a few-step autoregressive streaming model and introduces lightweight distilled codecs for efficient latent encoding and frame reconstruction. It retains the teacher model's G-buffer and text-prompt interfaces while enabling continuous rendering over input streams of unbounded length. We evaluate AlayaRenderer-Flash on G-buffer streams across content preservation, temporal consistency, cross-window stability, prompt controllability, and runtime efficiency. Our results show that AlayaRenderer-Flash substantially reduces inference cost while preserving the core rendering capabilities of the teacher model. By integrating AlayaRenderer-Flash with a physics engine, we build a fully playable generative world running at 30 FPS.
CommentsProject page: https://alaya-renderer-flash.alayalab.ai/
