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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Measuring Social Biases in Grounded Vision and Language Embeddings · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2002.08911/</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/2002.08911/feed.xml" rel="self" type="application/rss+xml" /><item><title>Measuring Social Biases in Grounded Vision and Language Embeddings — mentioned by 0xab</title><link>https://news.ycombinator.com/item?id=44176315</link><guid isPermaLink="false">urn:hackerpapers:mention:2002.08911:44176315</guid><pubDate>Wed, 04 Jun 2025 01:00:28 GMT</pubDate><description>&lt;p&gt;&amp;gt; When VLMs make errors, they don&amp;#x27;t make random mistakes. Instead, 75.70% of all errors are &amp;quot;bias-aligned&amp;quot; - meaning they give the expected answer based on prior knowledge rather than what they actually see in the image. Yeah, that&amp;#x27;s exactly what our paper said 5 years ago! They didn&amp;#x27;t even cite us :( &amp;quot;Measuring Social Biases in Grounded Vision and Language Embeddings&amp;quot; https://arxiv.org/pdf/2002.08911&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2002.08911/"&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>
