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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Deep Bidirectional Language-Knowledge Graph Pretraining · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2210.09338/</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/2210.09338/feed.xml" rel="self" type="application/rss+xml" /><item><title>Deep Bidirectional Language-Knowledge Graph Pretraining — mentioned by haldujai</title><link>https://news.ycombinator.com/item?id=33861916</link><guid isPermaLink="false">urn:hackerpapers:mention:2210.09338:33861916</guid><pubDate>Mon, 05 Dec 2022 05:46:32 GMT</pubDate><description>&lt;p&gt;Thank you for posting this. I’m not sure why but it seems like very few of the ChatGPT threads I’ve read across on Twitter/HN showing “very accurate and intelligent” results never experiment with ablation which is very important in prompt engineering and when evaluating DL models. I’m very excited about transformer based LLMs and use them extensively in my research and I think their generated content is good, but no where near being perfect or an imminent threat to society as people are worried about. There are several fundamental limitations in their training that prevent this from happening…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2210.09338/"&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>
