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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2010.00763/</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/2010.00763/feed.xml" rel="self" type="application/rss+xml" /><item><title>Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning — HN submission</title><link>https://news.ycombinator.com/item?id=25718174</link><guid isPermaLink="false">urn:hackerpapers:submission:2010.00763:25718174</guid><pubDate>Sun, 10 Jan 2021 18:59:00 GMT</pubDate><description>&lt;p&gt;My blog got cited by a NIPS paper&lt;/p&gt;&lt;p&gt;Few years back I wrote a post about a side project about applying deep learning to visual puzzles solving (k10v.github.io). Happy to learn now that it was cited by a recent paper, I hope that it shows that non-academic research is taken more seriously now. https://arxiv.org/abs/2010.00763 [24] S. Kharagorgiev, “Solving bongard problems with deep learning,” k10v.github.io, 2020&lt;/p&gt;&lt;p&gt;36 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2010.00763/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
