<?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>向量 on Plbear | 后端架构 · AI工程 · 云原生技术博客</title><link>https://www.plbear.com/tags/%E5%90%91%E9%87%8F/</link><description>Recent content in 向量 on Plbear | 后端架构 · AI工程 · 云原生技术博客</description><generator>Hugo</generator><language>zh-cn</language><lastBuildDate>Tue, 10 Jun 2025 09:00:00 +0800</lastBuildDate><atom:link href="https://www.plbear.com/tags/%E5%90%91%E9%87%8F/index.xml" rel="self" type="application/rss+xml"/><item><title>RAG 工程化：从切分到重排的调优实录</title><link>https://www.plbear.com/posts/2025-06-10-rag-engineering-tuning/</link><pubDate>Tue, 10 Jun 2025 09:00:00 +0800</pubDate><guid>https://www.plbear.com/posts/2025-06-10-rag-engineering-tuning/</guid><description>RAG demo 人人都能做，生产级 RAG 到处都是坑：切分粒度、召回策略、重排、上下文压缩。用招聘知识库做案例，把检索准确率从 55% 调到 85% 的完整记录。</description></item></channel></rss>