<?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>VLA on Xu'Blog</title><link>https://xuquant.com/tags/vla/</link><description>Recent content in VLA on Xu'Blog</description><image><title>Xu'Blog</title><url>https://xuquant.com/images/profile.jpg</url><link>https://xuquant.com/images/profile.jpg</link></image><generator>Hugo -- 0.152.2</generator><language>en</language><lastBuildDate>Sun, 11 Jan 2026 10:00:00 +0800</lastBuildDate><atom:link href="https://xuquant.com/tags/vla/index.xml" rel="self" type="application/rss+xml"/><item><title>Vision-Language-Action Models for Autonomous Driving: The Cosmos-Reason Approach</title><link>https://xuquant.com/posts/autodrive/nvidia_vla/</link><pubDate>Sun, 11 Jan 2026 10:00:00 +0800</pubDate><guid>https://xuquant.com/posts/autodrive/nvidia_vla/</guid><description>Technical deep-dive into Nvidia&amp;#39;s Cosmos-Reason (Alpamayo) VLA system for autonomous driving, covering tri-plane vision encoding, ego-shortcut avoidance, Cause-of-Change dataset paradigm, and reasoning-action alignment via reinforcement learning.</description></item><item><title>End-to-End Autonomous Driving: From Modular Decoders to VLA Architectures</title><link>https://xuquant.com/posts/autodrive/e2e-autonomous-driving-evolution/</link><pubDate>Thu, 01 May 2025 10:00:00 +0800</pubDate><guid>https://xuquant.com/posts/autodrive/e2e-autonomous-driving-evolution/</guid><description>A technical survey on the architectural evolution of end-to-end autonomous driving, covering planner decoder selection (AR vs Diffusion vs Flow Matching), VLA integration strategies, and engineering best practices for data infrastructure, training optimization, and evaluation systems.</description></item></channel></rss>