English(EN) WorldCache: Accelerating World Models for Free via Heterogeneous Token Caching

WorldCache 将扩散世界模型速度提升 3.7 倍

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-02 04:00

研究人员开发了 WorldCache，这是一个旨在加速基于扩散的世界模型的新缓存框架。该系统解决了这些模型固有的令牌异构性和非均匀时间动态等挑战。通过采用曲率引导的异构令牌预测和混沌优先的自适应跳过，WorldCache 在保持 98% 的滚动质量的同时，实现了高达 3.7 倍的速度提升。 AI

影响加速扩散世界模型，实现更高效的模拟和长时预测。

排序理由该集群包含一篇详细介绍加速 AI 模型新方法的 ist 研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Weilun Feng, Guoxin Fan, Haotong Qin, Mingqiang Wu, Yuqi Li, Xiangqi Li, Zhulin An, Libo Huang, Dingrui Wang, Longlong Liao, Michele Magno, Yongjun Xu, Chuanguang Yang · 2026-06-02 04:00

WorldCache：通过异构令牌缓存免费加速世界模型

arXiv:2603.06331v2 Announce Type: replace Abstract: Diffusion-based world models have shown strong potential for unified world simulation, but the iterative denoising remains too costly for interactive use and long-horizon rollouts. While feature caching can accelerate inference …