<?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>LMSYS on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/lmsys/</link><description>Recent content in LMSYS on 硅基 AGI · 智能体学习与测评</description><generator>Hugo</generator><language>zh-cn</language><copyright>本站内容采用 CC BY-NC-SA 4.0 国际许可协议授权</copyright><lastBuildDate>Wed, 24 Jun 2026 14:00:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/lmsys/index.xml" rel="self" type="application/rss+xml"/><item><title>主流 LLM 排行榜深度分析：谁是真正的 No.1？</title><link>https://guijiagi.com/posts/llm-leaderboard-analysis/</link><pubDate>Wed, 24 Jun 2026 14:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/llm-leaderboard-analysis/</guid><description>对比 LMSYS、OpenCompass、HELM、SuperCLUE 等主流排行榜的机制差异，教你如何选择参考榜单</description></item></channel></rss>