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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2409.13731/</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/2409.13731/feed.xml" rel="self" type="application/rss+xml" /><item><title>KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation — mentioned by badmonster</title><link>https://news.ycombinator.com/item?id=43980090</link><guid isPermaLink="false">urn:hackerpapers:mention:2409.13731:43980090</guid><pubDate>Wed, 14 May 2025 02:27:25 GMT</pubDate><description>&lt;p&gt;In my understanding, there are two kinds of use cases potentially can be explored with knowledge graph. - Structured data - this is probably more close to the use case you mention - Unstructure data and extract relationship and build KG with natural language understanding - which is this article trying to explore. Here is a paper discussing about this https://arxiv.org/abs/2409.13731 In general it is an alternative way to establish connections with entities easily. And these relationships could help with discovery, recommendation and retrieval. Thanks @alexchantavy for sharing use-cases in…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2409.13731/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation — mentioned by flimflamm</title><link>https://news.ycombinator.com/item?id=42548901</link><guid isPermaLink="false">urn:hackerpapers:mention:2409.13731:42548901</guid><pubDate>Mon, 30 Dec 2024 12:58:30 GMT</pubDate><description>&lt;p&gt;Paper also here https://arxiv.org/pdf/2409.13731&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2409.13731/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
