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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>WinoGrande: An Adversarial Winograd Schema Challenge at Scale · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1907.10641/</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/1907.10641/feed.xml" rel="self" type="application/rss+xml" /><item><title>WinoGrande: An Adversarial Winograd Schema Challenge at Scale — mentioned by mrconter11</title><link>https://news.ycombinator.com/item?id=42486271</link><guid isPermaLink="false">urn:hackerpapers:mention:1907.10641:42486271</guid><pubDate>Sun, 22 Dec 2024 13:47:15 GMT</pubDate><description>&lt;p&gt;Thank you for your reply. The time to human level is simply the time it took between the initial release of the website to when an AI system reached human level performance for that benchmark. :) I am in the process of adding sources for all &amp;quot;solved&amp;quot; dates... Here is for instance source for the Winograd challenge human level performance: https://arxiv.org/pdf/1907.10641#:~:text=The%20best%20state%...). :)&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1907.10641/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>WinoGrande: An Adversarial Winograd Schema Challenge at Scale — mentioned by YeGoblynQueenne</title><link>https://news.ycombinator.com/item?id=41538930</link><guid isPermaLink="false">urn:hackerpapers:mention:1907.10641:41538930</guid><pubDate>Sat, 14 Sep 2024 10:59:15 GMT</pubDate><description>&lt;p&gt;&amp;quot;Designed&amp;quot; is not right. What gives &amp;quot;AI models&amp;quot; (i.e. deep neural nets) a hard time is that there are very few examples in the public training and evaluation set: each task has three examples. So basically it&amp;#x27;s not a test of intelligence but a test of sample efficiency. Besides which, it is unfair because it excludes an entire category of systems, not to mention a dominant one. If F. Chollet really believes ARC is a test of intelligence, then why not provide enough examples for deep nets or some other big data approach to be trained effectively? The answer is: because a big data approach…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1907.10641/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>WinoGrande: An Adversarial Winograd Schema Challenge at Scale — HN submission</title><link>https://news.ycombinator.com/item?id=20539586</link><guid isPermaLink="false">urn:hackerpapers:submission:1907.10641:20539586</guid><pubDate>Sat, 27 Jul 2019 00:36:33 GMT</pubDate><description>&lt;p&gt;Winogrande: An Adversarial Winograd Schema Challenge at Scale&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1907.10641/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
