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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1903.03862/</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/1903.03862/feed.xml" rel="self" type="application/rss+xml" /><item><title>Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them — mentioned by spindump8930</title><link>https://news.ycombinator.com/item?id=43989060</link><guid isPermaLink="false">urn:hackerpapers:mention:1903.03862:43989060</guid><pubDate>Wed, 14 May 2025 20:49:39 GMT</pubDate><description>&lt;p&gt;First off, this interface is very nice and a pleasure to use, congrats! Are you using word2vec for these, or embeddings from another model? I also wanted to add some flavor since it looks like many folks in this thread haven&amp;#x27;t seen something like this - it&amp;#x27;s been known since 2013 that we can do this (but it&amp;#x27;s great to remind folks especially with all the &amp;quot;modern&amp;quot; interest in NLP). It&amp;#x27;s also known (in some circles!) that a lot of these vector arithmetic things need some tricks to really shine. For example, excluding the words already present in the query[1]. Others in this thread seem…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1903.03862/"&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>
