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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>What is the Impact of Releasing Code with Publications? Statistics from the Machine Learning, Robotics, and Control Communities · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2308.10008/</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/2308.10008/feed.xml" rel="self" type="application/rss+xml" /><item><title>What is the Impact of Releasing Code with Publications? Statistics from the Machine Learning, Robotics, and Control Communities — mentioned by ianm218</title><link>https://news.ycombinator.com/item?id=48738687</link><guid isPermaLink="false">urn:hackerpapers:mention:2308.10008:48738687</guid><pubDate>Tue, 30 Jun 2026 20:24:27 GMT</pubDate><description>&lt;p&gt;Just as a counterpoint ML and AI research has become much more reproducible over time. I feel like this is relevant because ML / AI researchers are huge power users of AI tools. Between 2016 and 2021 the share of ML/ robotics/ AI researchers being reproducible (ie contianing code and similar instructions to reproduce) doubled [1]. The major US labs have gone largely closed source (I.e. they no longer publish frontier research) but the Chinese ecosystem has incredibly reproducible code. This is field dependent obviously but I think it atleast gives reason to be optimistic. Yes people will…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2308.10008/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>eess.SY</category></item></channel></rss>
