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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Variational Pretraining for Semi-supervised Text Classification · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1906.02242/</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/1906.02242/feed.xml" rel="self" type="application/rss+xml" /><item><title>Variational Pretraining for Semi-supervised Text Classification — mentioned by rococode</title><link>https://news.ycombinator.com/item?id=22038795</link><guid isPermaLink="false">urn:hackerpapers:mention:1906.02242:22038795</guid><pubDate>Mon, 13 Jan 2020 21:25:19 GMT</pubDate><description>&lt;p&gt;They don&amp;#x27;t use huggingface, but some of the modern approaches for topic modeling use variational auto-encoders, see: Open-SESAME (2017): https://arxiv.org/abs/1706.09528 / https://github.com/swabhs/open-sesame VAMPIRE (2019): https://arxiv.org/abs/1906.02242 / https://github.com/allenai/vampire&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1906.02242/"&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>
