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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Blended RAG: Improving RAG (Retriever-Augmented Generation) Accuracy with Semantic Search and Hybrid Query-Based Retrievers · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2404.07220/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2404.07220/feed.xml" rel="self" type="application/rss+xml" /><item><title>Blended RAG: Improving RAG (Retriever-Augmented Generation) Accuracy with Semantic Search and Hybrid Query-Based Retrievers — mentioned by yingfeng</title><link>https://news.ycombinator.com/item?id=40982560</link><guid isPermaLink="false">urn:hackerpapers:mention:2404.07220:40982560</guid><pubDate>Wed, 17 Jul 2024 04:30:52 GMT</pubDate><description>&lt;p&gt;A noticeble work to demostrate the effectiveness of hybrid search is blended rag by IBM research (https://arxiv.org/abs/2404.07220), which has shown that 3-way hybrid search could achieve STOA over multiple evaluation datasets. And also, we&amp;#x27;ve reproduced the results of blended rag, as shown in this article. Additionally, blended rag + colbert based reranker could have a much better results. The major challenges are how to implement and manage such many indices within single database. That&amp;#x27;s why we build this database start from scratch. Infinity is actually a kind of &amp;quot;indexing&amp;quot; database…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2404.07220/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.IR</category></item></channel></rss>
