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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Modifying Large Language Model Post-Training for Diverse Creative Writing · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2503.17126/</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/2503.17126/feed.xml" rel="self" type="application/rss+xml" /><item><title>Modifying Large Language Model Post-Training for Diverse Creative Writing — mentioned by ijk</title><link>https://news.ycombinator.com/item?id=45478235</link><guid isPermaLink="false">urn:hackerpapers:mention:2503.17126:45478235</guid><pubDate>Sun, 05 Oct 2025 01:45:15 GMT</pubDate><description>&lt;p&gt;That&amp;#x27;s consistent with other research I&amp;#x27;ve seen, where varied presentation of the data is key to effective knowledge injection [1]. My assumption, based on the research is that training on different prompts but the same answer gives you more robust Q&amp;amp;A behavior; training on variations of how to express the same concept generalizes. Training on the same prompt and different answers gives you creative diversity [2]. [1] https://arxiv.org/abs/2404.00213 [2] https://arxiv.org/abs/2503.17126&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2503.17126/"&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>
