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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Quality-Diversity through AI Feedback · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2310.13032/</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/2310.13032/feed.xml" rel="self" type="application/rss+xml" /><item><title>Quality-Diversity through AI Feedback — mentioned by emadm</title><link>https://news.ycombinator.com/item?id=39366336</link><guid isPermaLink="false">urn:hackerpapers:mention:2310.13032:39366336</guid><pubDate>Wed, 14 Feb 2024 04:06:08 GMT</pubDate><description>&lt;p&gt;We are starting to see that, see phi2 for example There are approaches to get the right type of augmented and generated data to feed these models right, check out our QDAIF paper we worked on for example https://arxiv.org/pdf/2310.13032.pdf&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2310.13032/"&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>
