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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Towards Understanding and Mitigating Social Biases in Language Models · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2106.13219/</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/2106.13219/feed.xml" rel="self" type="application/rss+xml" /><item><title>Towards Understanding and Mitigating Social Biases in Language Models — mentioned by seanhunter</title><link>https://news.ycombinator.com/item?id=36444325</link><guid isPermaLink="false">urn:hackerpapers:mention:2106.13219:36444325</guid><pubDate>Fri, 23 Jun 2023 08:41:45 GMT</pubDate><description>&lt;p&gt;I&amp;#x27;m not sure what exactly you mean by censorship here because nothing that I know of that they do is actually censorship. In particular they don&amp;#x27;t do the sort of prompt stuffing you&amp;#x27;re talking about, because that would just use up the context window of the LLM and you&amp;#x27;d know because the context window is public and as a dev you can use the whole window. There is a &amp;quot;system&amp;quot; role that allows application developers to &amp;quot;whisper in the ear&amp;quot; of the LLM and provide prompts into the context that are different from the user prompts. That&amp;#x27;s how you build chat apps where you have a user providing some…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2106.13219/"&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>
