<rss xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title>Rag - 标签 - 研发日志 · R&amp;D Log</title><link>https://rd163.visword.com/tags/rag/</link><description>Rag - 标签 - 研发日志 · R&amp;D Log</description><generator>Hugo -- gohugo.io</generator><language>zh-CN</language><managingEditor>whutluohui@gmail.com (小智晖)</managingEditor><webMaster>whutluohui@gmail.com (小智晖)</webMaster><copyright>本作品采用知识共享署名-非商业性使用 4.0 国际许可协议进行许可。</copyright><lastBuildDate>Fri, 14 Feb 2025 00:00:00 +0800</lastBuildDate><atom:link href="https://rd163.visword.com/tags/rag/" rel="self" type="application/rss+xml"/><item><title>LLM Retrieval-Augmented Generation(RAG)</title><link>https://rd163.visword.com/posts/llm-retrieval-augmented-generation/</link><pubDate>Fri, 14 Feb 2025 00:00:00 +0800</pubDate><author><name>小智晖</name></author><guid>https://rd163.visword.com/posts/llm-retrieval-augmented-generation/</guid><description><![CDATA[<p>相关论文：<a href="https://arxiv.org/abs/2005.11401" target="_blank" rel="noopener noreferrer">Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks</a>
这里有个 <a href="https://github.com/SmartFlowAI/Hand-on-RAG" target="_blank" rel="noopener noreferrer">手搓的RAG</a> github项目可以一窥RAG的全貌。</p>
<h2 id="什么是检索增强生成" class="headerLink">
    <a href="#%e4%bb%80%e4%b9%88%e6%98%af%e6%a3%80%e7%b4%a2%e5%a2%9e%e5%bc%ba%e7%94%9f%e6%88%90" class="header-mark"></a>什么是检索增强生成？</h2><p>检索增强生成（RAG）是一个概念，它旨在为大语言模型（LLM）提供额外的、来自外部知识源的信息。这样，LLM 在生成更精确、更贴合上下文的答案的同时，也能有效减少产生误导性信息的可能。</p>]]></description></item></channel></rss>