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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Transformers as Soft Reasoners over Language · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2002.05867/</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/2002.05867/feed.xml" rel="self" type="application/rss+xml" /><item><title>Transformers as Soft Reasoners over Language — mentioned by andreyk</title><link>https://news.ycombinator.com/item?id=22350109</link><guid isPermaLink="false">urn:hackerpapers:mention:2002.05867:22350109</guid><pubDate>Mon, 17 Feb 2020 19:46:32 GMT</pubDate><description>&lt;p&gt;Here&amp;#x27;s a link to the paper: https://arxiv.org/abs/2002.05867 Shortened Abstract: &amp;quot;AI has long pursued the goal of having systems reason over explicitly provided knowledge, but building suitable representations has proved challenging. Here we explore whether transformers can similarly learn to reason (or emulate reasoning), but using rules expressed in language, thus bypassing a formal representation. We provide the first demonstration that this is possible, and characterize the extent of this capability. To do this, we use a collection of synthetic datasets that test increasing levels of…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2002.05867/"&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>
