<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>How Can We Know What Language Models Know? · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1911.12543/</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/1911.12543/feed.xml" rel="self" type="application/rss+xml" /><item><title>How Can We Know What Language Models Know? — mentioned by gwern</title><link>https://news.ycombinator.com/item?id=23354461</link><guid isPermaLink="false">urn:hackerpapers:mention:1911.12543:23354461</guid><pubDate>Fri, 29 May 2020 19:29:43 GMT</pubDate><description>&lt;p&gt;&amp;gt; The article I linked to makes claims only about the model it tests and since it actually links to an online implementation, anyone can try to reproduce the results and see for themselves. And I did (using my own local GPT-2-1.5b install which let me set the hyperparameters rather than restricting it to inappropriate hardwired ones of an online service), I linked to another person demonstrating the same thing, I pointed out the extensive GPT-3 evaluation OA did, and here, have another link about how bad querying of language models leads to highly misleading results about how much they know…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1911.12543/"&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>
