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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Optimizing the Interface Between Knowledge Graphs and LLMs for Complex Reasoning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2505.24478/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:27:26 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2505.24478/feed.xml" rel="self" type="application/rss+xml" /><item><title>Optimizing the Interface Between Knowledge Graphs and LLMs for Complex Reasoning — HN submission</title><link>https://news.ycombinator.com/item?id=44169594</link><guid isPermaLink="false">urn:hackerpapers:submission:2505.24478:44169594</guid><pubDate>Tue, 03 Jun 2025 13:05:15 GMT</pubDate><description>&lt;p&gt;Show HN: Cognee – Open-Source AI Memory Layer That Remembers Context&lt;/p&gt;&lt;p&gt;Hey HN! We&amp;#x27;re Vasilije, Laszlo and Lazar, the authors of a new paper and part of https://www.cognee.ai. cognee let’s you build memory layers for AI applications and agents, allowing them to personalize results, connect various data sources, and add custom rules. This enables AI apps to deliver increasingly accurate responses, we reached almost 90% on standard industry benchmarks as you can see here https://github.com/topoteretes/cognee/tree/main/evals and our paper can be accessed at: https://arxiv.org/abs/2505.24478 and collab is in the repository LLMs don&amp;#x27;t remember context well—they can’t…&lt;/p&gt;&lt;p&gt;9 points; 2 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2505.24478/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
