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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2507.17746/</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/2507.17746/feed.xml" rel="self" type="application/rss+xml" /><item><title>Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains — mentioned by nbardy</title><link>https://news.ycombinator.com/item?id=48890527</link><guid isPermaLink="false">urn:hackerpapers:mention:2507.17746:48890527</guid><pubDate>Mon, 13 Jul 2026 10:28:55 GMT</pubDate><description>&lt;p&gt;These are true and it does make theses fields the first to fall, but also the hype comes form the fact that it can escape these conditions as well: - generalize to non verifiable domains (https://arxiv.org/abs/2507.17746)[This is on going work but has had steady progress in many angles of attack) - Visual Reasoning is alive and well in video diffusion and image models(see recent works around using diffusion model priors as world model features for physics reasoning) - Prior art exists for anything humans can do online?(Is this one even a hold back?)&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2507.17746/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains — mentioned by jmalicki</title><link>https://news.ycombinator.com/item?id=48610193</link><guid isPermaLink="false">urn:hackerpapers:mention:2507.17746:48610193</guid><pubDate>Sat, 20 Jun 2026 15:55:50 GMT</pubDate><description>&lt;p&gt;The most advanced training data is in the form of rubrics as rewards. A human asks a question, then writes rubrics to judge the LLMs response, so rather than evaluating a specific response, those rubrics can live on as the LLM evolves and gives different answers. There are more complex variants as well, but that&amp;#x27;s the basic principle. https://arxiv.org/abs/2507.17746&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2507.17746/"&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>
