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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Foundation Models for Natural Language Processing -- Pre-trained Language Models Integrating Media · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2302.08575/</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/2302.08575/feed.xml" rel="self" type="application/rss+xml" /><item><title>Foundation Models for Natural Language Processing -- Pre-trained Language Models Integrating Media — mentioned by sfriedr</title><link>https://news.ycombinator.com/item?id=36337919</link><guid isPermaLink="false">urn:hackerpapers:mention:2302.08575:36337919</guid><pubDate>Thu, 15 Jun 2023 08:51:56 GMT</pubDate><description>&lt;p&gt;Congratulation, great paper! It should have been put on HN earlier ;) I have a few questions: * you say (page 4): &amp;quot;We then perform standard instruction finetuning on the base LLaMA-7B model&amp;quot; Could you perhaps provide a reference to the _exact_ finetuning approach you used? I&amp;#x27;m afraid different groups of people have a different notion of &amp;quot;standart&amp;quot; (see for example pages 131-155 from https://arxiv.org/abs/2302.08575 for various fine-tuning approaches) and without knowing exactly how fine-tuning was carried out, it can be very difficult reproduce your research and results exactly. * the idea of…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2302.08575/"&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>
