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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Large Language Models Can Follow Instructions, But Not Many at Once: Phase Transitions in Compositional Constraint Satisfaction · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2608.12426/</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/2608.12426/feed.xml" rel="self" type="application/rss+xml" /><item><title>Large Language Models Can Follow Instructions, But Not Many at Once: Phase Transitions in Compositional Constraint Satisfaction — mentioned by MrCoffee7</title><link>https://news.ycombinator.com/item?id=49688984</link><guid isPermaLink="false">urn:hackerpapers:mention:2608.12426:49688984</guid><pubDate>Sun, 13 Sep 2026 21:37:19 GMT</pubDate><description>&lt;p&gt;This paper wasn&amp;#x27;t for SKILLS per se, but for LLMs, and suggests that LLMs can&amp;#x27;t follow too many constraints at one time very well https://arxiv.org/abs/2608.12426 . Other papers suggest that LLMs show more information sparsity in the results with negative constraints.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2608.12426/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
