<?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>对比分析 on 硅基 AGI · 智能体学习与测评</title><link>https://guijiagi.com/tags/%E5%AF%B9%E6%AF%94%E5%88%86%E6%9E%90/</link><description>Recent content in 对比分析 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>Tue, 30 Jun 2026 09:40:00 +0800</lastBuildDate><atom:link href="https://guijiagi.com/tags/%E5%AF%B9%E6%AF%94%E5%88%86%E6%9E%90/index.xml" rel="self" type="application/rss+xml"/><item><title>RAG vs Long Context：何时用检索增强何时用长上下文</title><link>https://guijiagi.com/posts/rag-vs-long-context-comparison/</link><pubDate>Tue, 30 Jun 2026 09:40:00 +0800</pubDate><guid>https://guijiagi.com/posts/rag-vs-long-context-comparison/</guid><description>深度对比RAG与长上下文模型的优劣势，通过实测数据给出清晰的选型决策框架</description></item><item><title>思维链变体对比分析</title><link>https://guijiagi.com/posts/cot-variants-comparison/</link><pubDate>Sat, 27 Jun 2026 15:00:00 +0800</pubDate><guid>https://guijiagi.com/posts/cot-variants-comparison/</guid><description>Zero-shot CoT、Few-shot CoT、Auto-CoT等思维链变体的深度对比与选型指南</description></item></channel></rss>