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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>On the Possibilities of AI-Generated Text Detection · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2304.04736/</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/2304.04736/feed.xml" rel="self" type="application/rss+xml" /><item><title>On the Possibilities of AI-Generated Text Detection — mentioned by vminvsky</title><link>https://news.ycombinator.com/item?id=36438402</link><guid isPermaLink="false">urn:hackerpapers:mention:2304.04736:36438402</guid><pubDate>Thu, 22 Jun 2023 20:25:45 GMT</pubDate><description>&lt;p&gt;according to the paper they get 98% accuracy. another recent paper came out saying it&amp;#x27;s always possible to discriminate between real and synthetic text [1]. i think the core problem is with the generalist classifiers (gptzero, openai detector, etc). ex. openai&amp;#x27;s classifier has an accuracy of around 25% on it&amp;#x27;s own text. however, when you train a bespoke classifier (like the authors did), you can get really good results. [1] https://arxiv.org/pdf/2304.04736.pdf&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2304.04736/"&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>
