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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Backtracking Improves Generation Safety · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2409.14586/</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/2409.14586/feed.xml" rel="self" type="application/rss+xml" /><item><title>Backtracking Improves Generation Safety — mentioned by ebalit</title><link>https://news.ycombinator.com/item?id=41739850</link><guid isPermaLink="false">urn:hackerpapers:mention:2409.14586:41739850</guid><pubDate>Fri, 04 Oct 2024 10:12:28 GMT</pubDate><description>&lt;p&gt;I think this might be key, in addition to some landmark tokens to quickly backtrack to. The big question is how to train such model. There is a recent paper from Meta that propose a way to train a model to backtrack its generation to improve generation alignment [0]. [0] https://arxiv.org/html/2409.14586v1&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2409.14586/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
