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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>What Capable Agents Must Know: Selection Theorems for Robust Decision-Making under Uncertainty · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2603.02491/</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/2603.02491/feed.xml" rel="self" type="application/rss+xml" /><item><title>What Capable Agents Must Know: Selection Theorems for Robust Decision-Making under Uncertainty — mentioned by benlivengood</title><link>https://news.ycombinator.com/item?id=48808662</link><guid isPermaLink="false">urn:hackerpapers:mention:2603.02491:48808662</guid><pubDate>Mon, 06 Jul 2026 18:35:50 GMT</pubDate><description>&lt;p&gt;What I look forward to after research like https://arxiv.org/abs/2603.02491, which demonstrate the necessity of world-modeling capability to achieve satisfactory performance on certain goals, is a refractor the SoTA test suites to demonstrate how much world-modeling is necessary in various task distributions. There have been a few years now of arguments about the level to which transformers do or do not have a world model (v.s. being purely stochastic parrots like early pre-trained LLMs) and now we have some tools to actually make quantifiable determinations.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2603.02491/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
