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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Deep Learning to Detect Redundant Method Comments · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1806.04616/</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/1806.04616/feed.xml" rel="self" type="application/rss+xml" /><item><title>Deep Learning to Detect Redundant Method Comments — mentioned by mallamanis</title><link>https://news.ycombinator.com/item?id=21091215</link><guid isPermaLink="false">urn:hackerpapers:mention:1806.04616:21091215</guid><pubDate>Fri, 27 Sep 2019 12:38:11 GMT</pubDate><description>&lt;p&gt;[I&amp;#x27;m one of the Microsoft Research people who worked on this] Thanks for your questions! We have thought of many heuristics but we didn&amp;#x27;t want to constrain the dataset release on some heuristic that we picked, possibly ruining the dataset. Participants in the challenge should feel free to apply additional filters as they see fit. For example, this [1] work could be useful as a filtering method. Unfortunately, we do not have the budget to provide any compute resources to help with running the models at this time. Note that any techniques developed with this dataset will be owned by those who…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1806.04616/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.SE</category></item></channel></rss>
