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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2510.01171/</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/2510.01171/feed.xml" rel="self" type="application/rss+xml" /><item><title>Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity — mentioned by 986aignan</title><link>https://news.ycombinator.com/item?id=50202700</link><guid isPermaLink="false">urn:hackerpapers:mention:2510.01171:50202700</guid><pubDate>Thu, 22 Oct 2026 23:47:52 GMT</pubDate><description>&lt;p&gt;&amp;gt; Everything that comes from an LLM is a human expression, on some level, but if you asked a sampling of humans the same question I wonder if it would come out the same way. How would you explain the difference? What makes that answer more probable? RLHF has a way of squashing variance. If the different models are trained on each other or on the same human feedback, then the training would reduce the variety of answers while the similarity of feedback would lead the common answer to be similar. The different models may prefer the same controversial takes for the same reason that they tend to…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2510.01171/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity — mentioned by networked</title><link>https://news.ycombinator.com/item?id=48786914</link><guid isPermaLink="false">urn:hackerpapers:mention:2510.01171:48786914</guid><pubDate>Sat, 04 Jul 2026 16:59:58 GMT</pubDate><description>&lt;p&gt;&amp;gt; What exactly about this contest and way of writing was enjoyable to you? I‘ve seen your very analytical approach for identifying a premise but then relatively little control about all the rest. The lack of control was the point. The contest was about improving autonomous AI fiction as opposed to the usual &amp;quot;centaur&amp;quot; AI fiction (named after &amp;quot;centaur chess&amp;quot; where the AI is steered by a human). My claude.ai harness for Unslop was designed to only take input on the first human turn. There were several exciting things for me about the contest. Let me try to list them, though I fully expect to…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2510.01171/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity — HN submission</title><link>https://news.ycombinator.com/item?id=46665183</link><guid isPermaLink="false">urn:hackerpapers:submission:2510.01171:46665183</guid><pubDate>Sun, 18 Jan 2026 05:59:29 GMT</pubDate><description>&lt;p&gt;Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;1 point; 2 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2510.01171/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity — HN submission</title><link>https://news.ycombinator.com/item?id=45815087</link><guid isPermaLink="false">urn:hackerpapers:submission:2510.01171:45815087</guid><pubDate>Tue, 04 Nov 2025 19:40:55 GMT</pubDate><description>&lt;p&gt;Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;1 point; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2510.01171/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity — HN submission</title><link>https://news.ycombinator.com/item?id=45763142</link><guid isPermaLink="false">urn:hackerpapers:submission:2510.01171:45763142</guid><pubDate>Thu, 30 Oct 2025 18:10:28 GMT</pubDate><description>&lt;p&gt;Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2510.01171/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item><item><title>Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity — HN submission</title><link>https://news.ycombinator.com/item?id=45631867</link><guid isPermaLink="false">urn:hackerpapers:submission:2510.01171:45631867</guid><pubDate>Sun, 19 Oct 2025 03:17:25 GMT</pubDate><description>&lt;p&gt;Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;3 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2510.01171/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
