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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hierarchical Reasoning Model · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2506.21734/</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/2506.21734/feed.xml" rel="self" type="application/rss+xml" /><item><title>Hierarchical Reasoning Model — mentioned by Balinares</title><link>https://news.ycombinator.com/item?id=45507782</link><guid isPermaLink="false">urn:hackerpapers:mention:2506.21734:45507782</guid><pubDate>Tue, 07 Oct 2025 19:36:49 GMT</pubDate><description>&lt;p&gt;Wow, so not only are the findings from https://arxiv.org/abs/2506.21734 (posted on HN a while back) confirmed, they&amp;#x27;re generalizable? Intriguing. I wonder if this will pan out in practical use cases, it&amp;#x27;d be transformative. Also would possibly instantly void the value of trillions of pending AI datacenter capex, which would be funny. (Though possibly not for very long.)&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2506.21734/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Hierarchical Reasoning Model — mentioned by mxkopy</title><link>https://news.ycombinator.com/item?id=45074035</link><guid isPermaLink="false">urn:hackerpapers:mention:2506.21734:45074035</guid><pubDate>Sat, 30 Aug 2025 12:27:26 GMT</pubDate><description>&lt;p&gt;There’s the hierarchical reasoning model https://arxiv.org/abs/2506.21734 but it’s very new and largely untested Though honestly I don’t think new neural network architectures are going to get us over this local maximum, I think the next steps forward involve something that’s 1. Non lossy 2. Readily interpretable&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2506.21734/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Hierarchical Reasoning Model — mentioned by mucho_mojo</title><link>https://news.ycombinator.com/item?id=44901687</link><guid isPermaLink="false">urn:hackerpapers:mention:2506.21734:44901687</guid><pubDate>Thu, 14 Aug 2025 15:35:00 GMT</pubDate><description>&lt;p&gt;This paper I read from here has an interesting mathematical model for reasoning based on cognitive science. https://arxiv.org/abs/2506.21734 (there is also code here https://github.com/sapientinc/HRM) I think we will see dramatic performance increases on &amp;quot;reasoning&amp;quot; problems when this is worked into existing AI architectures.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2506.21734/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Hierarchical Reasoning Model — mentioned by munro</title><link>https://news.ycombinator.com/item?id=44739689</link><guid isPermaLink="false">urn:hackerpapers:mention:2506.21734:44739689</guid><pubDate>Wed, 30 Jul 2025 21:26:09 GMT</pubDate><description>&lt;p&gt;Link to paper here https://arxiv.org/pdf/2506.21734 Still reading, but the benchmarks for ARC-AGI-1, ARC-AGI-2, Sudoku-Extreme (9x9), and Maze-Hard (30x30) look impressive.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2506.21734/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Hierarchical Reasoning Model — mentioned by westurner</title><link>https://news.ycombinator.com/item?id=44702554</link><guid isPermaLink="false">urn:hackerpapers:mention:2506.21734:44702554</guid><pubDate>Sun, 27 Jul 2025 16:42:52 GMT</pubDate><description>&lt;p&gt;sapientinc/HRM: Hierarchical Reasoning Model: https://github.com/sapientinc/HRM : &amp;gt; [...] Inspired by the hierarchical and multi-timescale processing in the human brain, we propose the Hierarchical Reasoning Model (HRM), a novel recurrent architecture that attains significant computational depth while maintaining both training stability and efficiency. HRM executes sequential reasoning tasks in a single forward pass without explicit supervision of the intermediate process, through two interdependent recurrent modules: a high-level module responsible for slow, abstract planning, and a…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2506.21734/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Hierarchical Reasoning Model — HN submission</title><link>https://news.ycombinator.com/item?id=44699452</link><guid isPermaLink="false">urn:hackerpapers:submission:2506.21734:44699452</guid><pubDate>Sun, 27 Jul 2025 07:15:57 GMT</pubDate><description>&lt;p&gt;Hierarchical Reasoning Model&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;339 points; 106 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2506.21734/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Hierarchical Reasoning Model — HN submission</title><link>https://news.ycombinator.com/item?id=44649792</link><guid isPermaLink="false">urn:hackerpapers:submission:2506.21734:44649792</guid><pubDate>Tue, 22 Jul 2025 16:48:35 GMT</pubDate><description>&lt;p&gt;Hierarchical Reasoning Model&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;9 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2506.21734/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Hierarchical Reasoning Model — mentioned by mingli_yuan</title><link>https://news.ycombinator.com/item?id=44646544</link><guid isPermaLink="false">urn:hackerpapers:mention:2506.21734:44646544</guid><pubDate>Tue, 22 Jul 2025 13:21:29 GMT</pubDate><description>&lt;p&gt;Hi HN, We&amp;#x27;ve seen LLMs struggle with complex, multi-step reasoning tasks. The common approach, Chain-of-Thought (CoT), often requires massive datasets, is brittle, and suffers from high latency. To tackle this, we developed the Hierarchical Reasoning Model (HRM), a novel recurrent architecture inspired by how the human brain processes information across different timescales (as seen in the diagram on the left). It&amp;#x27;s a small model that packs a huge punch. Here are the key highlights: Extremely Lightweight: Only 27 million parameters. Data Efficient: Trained with just 1000 samples for the…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2506.21734/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Hierarchical Reasoning Model — HN submission</title><link>https://news.ycombinator.com/item?id=44519661</link><guid isPermaLink="false">urn:hackerpapers:submission:2506.21734:44519661</guid><pubDate>Thu, 10 Jul 2025 11:12:16 GMT</pubDate><description>&lt;p&gt;HRM: 27M parameters, 1000 training samples, no pre-training required&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2506.21734/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item><item><title>Hierarchical Reasoning Model — HN submission</title><link>https://news.ycombinator.com/item?id=44461403</link><guid isPermaLink="false">urn:hackerpapers:submission:2506.21734:44461403</guid><pubDate>Fri, 04 Jul 2025 05:33:13 GMT</pubDate><description>&lt;p&gt;Hierarchical Reasoning Model&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2506.21734/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
