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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LogitScope: A Framework for Analyzing LLM Uncertainty Through Information Metrics · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2603.24929/</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/2603.24929/feed.xml" rel="self" type="application/rss+xml" /><item><title>LogitScope: A Framework for Analyzing LLM Uncertainty Through Information Metrics — mentioned by mncharity</title><link>https://news.ycombinator.com/item?id=49628807</link><guid isPermaLink="false">urn:hackerpapers:mention:2603.24929:49628807</guid><pubDate>Wed, 09 Sep 2026 16:08:18 GMT</pubDate><description>&lt;p&gt;Brief blog post, with picture of UI: https://plasticlabs.ai/blog/research/Plastic-Labs-at-ICLR-20... (site has an scroller bug with anchor seeking - relevant bit is half-way down the short page). Github: https://github.com/ibm-granite/granite.debug-tools/tree/main... Paper: LogitScope: A Framework for Analyzing LLM Uncertainty Through Information Metrics https://arxiv.org/abs/2603.24929&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2603.24929/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
