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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Language models show human-like content effects on reasoning tasks · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2207.07051/</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/2207.07051/feed.xml" rel="self" type="application/rss+xml" /><item><title>Language models show human-like content effects on reasoning tasks — mentioned by nl</title><link>https://news.ycombinator.com/item?id=34951592</link><guid isPermaLink="false">urn:hackerpapers:mention:2207.07051:34951592</guid><pubDate>Mon, 27 Feb 2023 00:46:34 GMT</pubDate><description>&lt;p&gt;Actually https://arxiv.org/pdf/2207.07051.pdf is DeepMind doing Wason (and other) tests on Chincilla and they find it scores between 40% and 60% on &amp;quot;realistic&amp;quot; and &amp;quot;shuffled realistic&amp;quot; Wason tests (I think. It&amp;#x27;s hard to read. See Figure 5).&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2207.07051/"&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>
