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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>A Knowledge-Grounded Neural Conversation Model · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1702.01932/</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/1702.01932/feed.xml" rel="self" type="application/rss+xml" /><item><title>A Knowledge-Grounded Neural Conversation Model — mentioned by abhgh</title><link>https://news.ycombinator.com/item?id=23417692</link><guid isPermaLink="false">urn:hackerpapers:mention:1702.01932:23417692</guid><pubDate>Thu, 04 Jun 2020 15:13:39 GMT</pubDate><description>&lt;p&gt;There has been some work in grounding NN conversations by either giving them factual memory/knowledge base - [1], [2],[3]. Personally I would love to see more work in this area where you have a robust language generator guided by a (1) high level task learner AND/OR (2) a knowledge base. [1] Commonsense Knowledge Aware Conversation Generation with Graph Attention https://www.ijcai.org/Proceedings/2018/0643.pdf [2] A Knowledge-Grounded Neural Conversation Model https://arxiv.org/pdf/1702.01932.pdf [3] Conversing by Reading:Contentful Neural Conversation with On-demand Machine Reading…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1702.01932/"&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>
