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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>RADLADS: Rapid Attention Distillation to Linear Attention Decoders at Scale · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2505.03005/</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/2505.03005/feed.xml" rel="self" type="application/rss+xml" /><item><title>RADLADS: Rapid Attention Distillation to Linear Attention Decoders at Scale — mentioned by killerstorm</title><link>https://news.ycombinator.com/item?id=43972401</link><guid isPermaLink="false">urn:hackerpapers:mention:2505.03005:43972401</guid><pubDate>Tue, 13 May 2025 12:54:17 GMT</pubDate><description>&lt;p&gt;Another paper related to attention distillation, although doing something far more radical: transformer attention is distilled onto RWKV-like model: https://huggingface.co/papers/2505.03005&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2505.03005/"&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>
