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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2402.13249/</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/2402.13249/feed.xml" rel="self" type="application/rss+xml" /><item><title>TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization — mentioned by nicklecompte</title><link>https://news.ycombinator.com/item?id=39767825</link><guid isPermaLink="false">urn:hackerpapers:mention:2402.13249:39767825</guid><pubDate>Wed, 20 Mar 2024 15:18:21 GMT</pubDate><description>&lt;p&gt;They’re good at summarizing text convincingly if you didn’t read the original document, but GPT-4 still makes a ton of basic factual mistakes: https://arxiv.org/abs/2402.13249 I think it will be several decades - maybe longer - before you can throw an arbitrary 20-page document into a computer program and get an accurate one-page summary. People need to take seriously that transformer LLMs don’t understand human language.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2402.13249/"&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>
