<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Video-Generation on Xu'Blog</title><link>https://xuquant.com/tags/video-generation/</link><description>Recent content in Video-Generation on Xu'Blog</description><image><title>Xu'Blog</title><url>https://xuquant.com/og-default.png</url><link>https://xuquant.com/og-default.png</link></image><generator>Hugo -- 0.152.2</generator><language>zh</language><lastBuildDate>Fri, 15 May 2026 10:00:00 +0800</lastBuildDate><atom:link href="https://xuquant.com/tags/video-generation/index.xml" rel="self" type="application/rss+xml"/><item><title>从预测未来到驱动行动：机器人世界模型的架构与评测</title><link>https://xuquant.com/posts/world-models/world-model-robot-learning/</link><pubDate>Fri, 15 May 2026 10:00:00 +0800</pubDate><guid>https://xuquant.com/posts/world-models/world-model-robot-learning/</guid><description>围绕 NTU/UC Berkeley/Stanford 联合综述 World Model for Robot Learning，从闭环动机、六范式对比、评测转向到一个关于 disentangled metric 的批判，把机器人世界模型放回本系列的正交视角之中。</description></item><item><title>Wan2.2 and the Boundary of Video World Models</title><link>https://xuquant.com/posts/world-models/wan2.2-video-world-model-boundary/</link><pubDate>Sat, 14 Mar 2026 10:00:00 +0800</pubDate><guid>https://xuquant.com/posts/world-models/wan2.2-video-world-model-boundary/</guid><description>Wan2.2 pushes video generation toward photorealistic world simulation, but where is the boundary between generating videos and understanding worlds? This article examines the architecture, training, and fundamental limits of video-based world models.</description></item><item><title>InSpatio-World: Real-Time 4D World Simulation via Spatiotemporal Autoregressive Modeling</title><link>https://xuquant.com/posts/foundation-models/inspatio-world-4d-simulator/</link><pubDate>Sat, 25 Oct 2025 10:00:00 +0800</pubDate><guid>https://xuquant.com/posts/foundation-models/inspatio-world-4d-simulator/</guid><description>InSpatio-World 深度技术分析：一个 13 亿参数的实时 4D 世界模拟器，通过隐式时空缓存与显式几何约束的结合，实现从单目视频以 24 FPS 进行新视角合成。</description></item></channel></rss>