<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Toward Ultra-Long-Horizon Agentic Science: Cognitive Accumulation for Machine Learning Engineering · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2601.10402/</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/2601.10402/feed.xml" rel="self" type="application/rss+xml" /><item><title>Toward Ultra-Long-Horizon Agentic Science: Cognitive Accumulation for Machine Learning Engineering — mentioned by Xx_crazy420_xX</title><link>https://news.ycombinator.com/item?id=47498739</link><guid isPermaLink="false">urn:hackerpapers:mention:2601.10402:47498739</guid><pubDate>Tue, 24 Mar 2026 04:55:53 GMT</pubDate><description>&lt;p&gt;Autoresearch is nothing new, big players are already in the game with more sophisticated solutions: - https://arxiv.org/abs/2602.02660 (MARS) - https://arxiv.org/abs/2601.14525 (Execution-grounded automated AI research) - https://arxiv.org/abs/2601.10402 (ML-Master 2.0) The mostly used benchmark for automated AI engineering/ research is: https://github.com/openai/mle-bench&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2601.10402/"&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>
