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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Progressive Sparse Attention: Algorithm and System Co-design for Efficient Attention in LLM Serving · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2503.00392/</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/2503.00392/feed.xml" rel="self" type="application/rss+xml" /><item><title>Progressive Sparse Attention: Algorithm and System Co-design for Efficient Attention in LLM Serving — mentioned by JPLeRouzic</title><link>https://news.ycombinator.com/item?id=49905760</link><guid isPermaLink="false">urn:hackerpapers:mention:2503.00392:49905760</guid><pubDate>Wed, 30 Sep 2026 07:49:44 GMT</pubDate><description>&lt;p&gt;I have read somewhere that Transformer architecture has a quadratic cost [0] (which explains the high costs associated with LLMs and the difficulty for constant improvement without state size pockets). For what I understand PSSA belongs to a line of research for LLMs with scalable architecture because you don&amp;#x27;t need to load the full KV in memory to generate a single token: [0] https://aclanthology.org/2023.findings-emnlp.936/ https://arxiv.org/abs/2503.00392 https://papers.nips.cc/paper_files/paper/2023/hash/6ceefa7b1...&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2503.00392/"&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>
