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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>DLGNet: A Transformer-based Model for Dialogue Response Generation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1908.01841/</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/1908.01841/feed.xml" rel="self" type="application/rss+xml" /><item><title>DLGNet: A Transformer-based Model for Dialogue Response Generation — mentioned by lettergram</title><link>https://news.ycombinator.com/item?id=21610319</link><guid isPermaLink="false">urn:hackerpapers:mention:1908.01841:21610319</guid><pubDate>Fri, 22 Nov 2019 21:33:12 GMT</pubDate><description>&lt;p&gt;From my own work: * NER (name-entity recognition) is becoming insanely good (99+%), this can help with everything from data security to automated form filling, to automated medical billing, etc. Multiple billion dollar industries will be shook up by this. * My own work on data generation is pointing to reduced surface area of security purposes and improved access to quasi-data for data science and application testing[1] * Translation from images to text descriptions are also a major thing, which when combined with other systems can do things like make suggested diagnosis. * Text generation…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1908.01841/"&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>
