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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>On Learning to Summarize with Large Language Models as References · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2305.14239/</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/2305.14239/feed.xml" rel="self" type="application/rss+xml" /><item><title>On Learning to Summarize with Large Language Models as References — mentioned by filterfiber</title><link>https://news.ycombinator.com/item?id=38476596</link><guid isPermaLink="false">urn:hackerpapers:mention:2305.14239:38476596</guid><pubDate>Thu, 30 Nov 2023 17:54:42 GMT</pubDate><description>&lt;p&gt;Yeah that&amp;#x27;s a fairly well studied one. Most of these techniques are rather &amp;quot;lossy&amp;quot; compared to extending the context window. The most likely &amp;quot;real solution&amp;quot; is going to be using various tricks and finetuning on higher context lengths to just extend the context window. Here&amp;#x27;s a bunch of other related methods, Summarizing context - https://arxiv.org/abs/2305.14239 continuous finetuning - https://arxiv.org/pdf/2307.02839.pdf retrieval augmented generation - https://arxiv.org/abs/2005.11401 knowledge graphs - https://arxiv.org/abs/2306.08302 augmenting the network a side network…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2305.14239/"&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>
