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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1910.13461/</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/1910.13461/feed.xml" rel="self" type="application/rss+xml" /><item><title>BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension — mentioned by deeplstm</title><link>https://news.ycombinator.com/item?id=28800533</link><guid isPermaLink="false">urn:hackerpapers:mention:1910.13461:28800533</guid><pubDate>Fri, 08 Oct 2021 15:46:19 GMT</pubDate><description>&lt;p&gt;BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension https://arxiv.org/abs/1910.13461 (paper) Code (Facebook) https://github.com/pytorch/fairseq/tree/main/examples/bart Code (Hugginface) https://huggingface.co/transformers/model_doc/bart.html&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1910.13461/"&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>
