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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>From task structures to world models: What do LLMs know? · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2310.04276/</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/2310.04276/feed.xml" rel="self" type="application/rss+xml" /><item><title>From task structures to world models: What do LLMs know? — mentioned by seanhunter</title><link>https://news.ycombinator.com/item?id=38390609</link><guid isPermaLink="false">urn:hackerpapers:mention:2310.04276:38390609</guid><pubDate>Thu, 23 Nov 2023 08:16:17 GMT</pubDate><description>&lt;p&gt;Actual reasoning shows the understanding and use of a model of the key features of the underlying problem/domain. As a simple example that you can replicate using chatgpt, ask it to solve some simple maths problem. Very frequently you will get a solution that looks like reasoning but is not, and reveals that it does not have an actual model of the underlying maths but is in fact doing text prediction based on a history of maths. For example see here[1]. I ask it for some quadratics in x with some specification on the number of roots. It gives me what looks at first glance like a decent…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2310.04276/"&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>
