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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Reinforced Large Language Model is a formal theorem prover · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2502.08908/</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/2502.08908/feed.xml" rel="self" type="application/rss+xml" /><item><title>Reinforced Large Language Model is a formal theorem prover — mentioned by mindwok</title><link>https://news.ycombinator.com/item?id=44167381</link><guid isPermaLink="false">urn:hackerpapers:mention:2502.08908:44167381</guid><pubDate>Tue, 03 Jun 2025 07:32:43 GMT</pubDate><description>&lt;p&gt;Sure, &amp;gt; In theoretical computer science, an algorithm is correct with respect to a specification if it behaves as specified. &amp;quot;As specified&amp;quot; here being the key phrase. This is defined however you want, and ranges from a person saying &amp;quot;yep, behaves as specified&amp;quot;, to a formal proof. Modern language language models are trained under RL for both sides of this spectrum, from &amp;quot;Hey man looks good&amp;quot;, to formal theorem proving. See https://arxiv.org/html/2502.08908v1. So I&amp;#x27;ll return to my original point: LLMs are not just generating outputs that look plausible, they are generating outputs that satisfy…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2502.08908/"&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>
