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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Beyond Partisan Leaning: A Comparative Analysis of Political Bias in Large Language Models · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2412.16746/</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/2412.16746/feed.xml" rel="self" type="application/rss+xml" /><item><title>Beyond Partisan Leaning: A Comparative Analysis of Political Bias in Large Language Models — mentioned by FunHearing3443</title><link>https://news.ycombinator.com/item?id=48838293</link><guid isPermaLink="false">urn:hackerpapers:mention:2412.16746:48838293</guid><pubDate>Wed, 08 Jul 2026 22:36:58 GMT</pubDate><description>&lt;p&gt;Studies on political bias in models consistently show that LLMs lean politically left. The only outlier is grok which leans right but by a smaller factor, according to this study for instance: https://arxiv.org/abs/2603.23841 Edit: adding some other studies that are easily retrievable with a quick search for those unsatisfied with the first one - https://arxiv.org/abs/2606.12922 https://arxiv.org/abs/2412.16746 Claiming reality has a left wing bias is certainly an opinion you&amp;#x27;re welcome to have to explain this, but the reality of the bias in models is well evidenced. It seems that practically…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2412.16746/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CY</category></item><item><title>Beyond Partisan Leaning: A Comparative Analysis of Political Bias in Large Language Models — HN submission</title><link>https://news.ycombinator.com/item?id=42623334</link><guid isPermaLink="false">urn:hackerpapers:submission:2412.16746:42623334</guid><pubDate>Tue, 07 Jan 2025 15:26:00 GMT</pubDate><description>&lt;p&gt;Political Bias in Large Language Models: Insights Across Topic Polarization&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;9 points; 2 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2412.16746/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CY</category></item></channel></rss>
