<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Divergent Creativity in Humans and Large Language Models · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2405.13012/</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/2405.13012/feed.xml" rel="self" type="application/rss+xml" /><item><title>Divergent Creativity in Humans and Large Language Models — mentioned by orbital-decay</title><link>https://news.ycombinator.com/item?id=41816381</link><guid isPermaLink="false">urn:hackerpapers:mention:2405.13012:41816381</guid><pubDate>Sat, 12 Oct 2024 04:20:51 GMT</pubDate><description>&lt;p&gt;You can also make Opus answer &amp;quot;Pick a random color (one word):&amp;quot; and watch it picking the same color or two most of the time. However this is a poor example of the point you&amp;#x27;re trying to make, as the lack of diversity in token prediction can have a ton of different root causes which are hard to separate. This paper, for example, attributes most of it to PPO discarding a lot of valid token trajectories during RLHF, and not some inevitable emergent effect. [1] [2] &amp;gt; only the largest Anthropic model is breaking from stochastic outputs there Most models, even small ones, exhibit the lack of output…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2405.13012/"&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>
