<?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>Paper-Reading on Xu'Blog</title><link>https://xuquant.com/en/tags/paper-reading/</link><description>Recent content in Paper-Reading 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>en</language><lastBuildDate>Sat, 22 Nov 2025 10:00:00 +0800</lastBuildDate><atom:link href="https://xuquant.com/en/tags/paper-reading/index.xml" rel="self" type="application/rss+xml"/><item><title>CORAL: Autonomous Multi-Agent Evolution for Open-Ended Discovery</title><link>https://xuquant.com/en/posts/foundation-models/coral-autonomous-multi-agent-evolution/</link><pubDate>Sat, 22 Nov 2025 10:00:00 +0800</pubDate><guid>https://xuquant.com/en/posts/foundation-models/coral-autonomous-multi-agent-evolution/</guid><description>How delegating evolutionary search decisions to autonomous agents—rather than relying on fixed heuristics—enables faster convergence and stronger results across mathematical and systems optimization tasks.</description></item><item><title>InSpatio-World: Real-Time 4D World Simulation via Spatiotemporal Autoregressive Modeling</title><link>https://xuquant.com/en/posts/foundation-models/inspatio-world-4d-simulator/</link><pubDate>Sat, 25 Oct 2025 10:00:00 +0800</pubDate><guid>https://xuquant.com/en/posts/foundation-models/inspatio-world-4d-simulator/</guid><description>A deep technical analysis of InSpatio-World: a 1.3B-parameter real-time 4D world simulator that combines implicit spatiotemporal caching with explicit geometric constraints, achieving 24 FPS novel-view synthesis from monocular video.</description></item><item><title>Alpamayo: Reasoning-Action Aligned VLA for Autonomous Driving</title><link>https://xuquant.com/en/posts/autonomous-driving/nvidia_vla/</link><pubDate>Sat, 30 Aug 2025 10:00:00 +0800</pubDate><guid>https://xuquant.com/en/posts/autonomous-driving/nvidia_vla/</guid><description>Technical deep-dive into Nvidia&amp;#39;s Alpamayo VLA system for autonomous driving, built on the Cosmos-Reason VLM backbone, covering tri-plane vision encoding, ego-shortcut avoidance, Cause-of-Change dataset paradigm, and reasoning-action alignment via reinforcement learning.</description></item></channel></rss>