<?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>模型效率 on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/%E6%A8%A1%E5%9E%8B%E6%95%88%E7%8E%87/</link><description>Recent content in 模型效率 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>Thu, 02 Jul 2026 11:08:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/%E6%A8%A1%E5%9E%8B%E6%95%88%E7%8E%87/index.xml" rel="self" type="application/rss+xml"/><item><title>混合分辨率：多尺度处理</title><link>https://guijiagi.com/posts/mixture-of-resolutions/</link><pubDate>Thu, 02 Jul 2026 11:08:00 +0800</pubDate><guid>https://guijiagi.com/posts/mixture-of-resolutions/</guid><description>解析多尺度分辨率处理如何提升模型效率与性能，以及在2026年的最新进展</description></item></channel></rss>