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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>How well do LLMs cite relevant medical references? An evaluation framework and analyses · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2402.02008/</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/2402.02008/feed.xml" rel="self" type="application/rss+xml" /><item><title>How well do LLMs cite relevant medical references? An evaluation framework and analyses — mentioned by simonw</title><link>https://news.ycombinator.com/item?id=39496410</link><guid isPermaLink="false">urn:hackerpapers:mention:2402.02008:39496410</guid><pubDate>Sun, 25 Feb 2024 00:23:36 GMT</pubDate><description>&lt;p&gt;&amp;quot;For the most advanced model (GPT-4 with retrieval augmented generation), 30% of individual statements are unsupported and nearly half of its responses are not fully supported&amp;quot; Show us the source code and data. The way the RAG system is implemented is responsible for that score. Building a RAG system that provides good citations on top of GPT-4 is difficult (and I would say not a fully solved problem at this point) but those implementation details still really matter for this kind of study. UPDATE: I found it in the paper: https://arxiv.org/html/2402.02008v1#S3 - &amp;quot;GPT-4 (RAG) refers to…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2402.02008/"&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>How well do LLMs cite relevant medical references? An evaluation framework and analyses — mentioned by panabee</title><link>https://news.ycombinator.com/item?id=39494261</link><guid isPermaLink="false">urn:hackerpapers:mention:2402.02008:39494261</guid><pubDate>Sat, 24 Feb 2024 19:09:52 GMT</pubDate><description>&lt;p&gt;full tweet since truncation was required for submission: Does #RAG/web search solve #LLM hallucinations? We find that even with RAG, 45% of responses by #GPT4 to medical queries are not fully supported by retrieved URLs. The problem is much worse for GPT-4 w/o RAG, #Gemini and #Claude arxiv.org/pdf/2402.02008… RAG ≠ faithful to source&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2402.02008/"&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>
