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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Causal Reasoning and Large Language Models: Opening a New Frontier for Causality · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2305.00050/</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/2305.00050/feed.xml" rel="self" type="application/rss+xml" /><item><title>Causal Reasoning and Large Language Models: Opening a New Frontier for Causality — mentioned by famouswaffles</title><link>https://news.ycombinator.com/item?id=36686553</link><guid isPermaLink="false">urn:hackerpapers:mention:2305.00050:36686553</guid><pubDate>Tue, 11 Jul 2023 20:06:02 GMT</pubDate><description>&lt;p&gt;&amp;gt;I doubt it, but according the the article, it&amp;#x27;s reasonable to assume the LLM would be progressively worse. I genuinely don&amp;#x27;t see how that would be a reasonable assumption. &amp;gt;Will humans do worse in base-3 than base-9? Why not? If you haven&amp;#x27;t learnt base 3 but you have base 9 you&amp;#x27;ll do poorer on it. &amp;gt;That, IMO, is an indicator that something different is going on. Whether something different is going on is about as relevant as the question of whether submarines swim or plans fly or cars run. &amp;gt;I.e., humans are deriving principles to work from rather than just pattern recognition. Not really.…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2305.00050/"&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>Causal Reasoning and Large Language Models: Opening a New Frontier for Causality — mentioned by chaxor</title><link>https://news.ycombinator.com/item?id=36065977</link><guid isPermaLink="false">urn:hackerpapers:mention:2305.00050:36065977</guid><pubDate>Thu, 25 May 2023 01:05:15 GMT</pubDate><description>&lt;p&gt;Perhaps, but taken with other works in the area, a better picture does emerge regarding this claim. Substantial works already showing reasoning capabilities in GPT-4, which show that these models do reason very well - near human performance for many causal reasoning tasks. (1) Additionally, there is a mathematical proof that these systems align with dynamic programming, and therefore can perform algorithmic reasoning. (2,3) 1) https://arxiv.org/abs/2305.00050.pdf 2) https://arxiv.org/pdf/1905.13211.pdf 3) https://arxiv.org/pdf/2203.15544.pdf&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2305.00050/"&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>Causal Reasoning and Large Language Models: Opening a New Frontier for Causality — mentioned by chaxor</title><link>https://news.ycombinator.com/item?id=36065950</link><guid isPermaLink="false">urn:hackerpapers:mention:2305.00050:36065950</guid><pubDate>Thu, 25 May 2023 01:01:18 GMT</pubDate><description>&lt;p&gt;There are substantial works already showing reasoning capabilities in GPT-4, which show that these models do reason extremely well - near human performance for many causal reasoning tasks. (1) Additionally, there is a mathematical proof that these systems align with dynamic programming, and therefore can do algorithmic reasoning. (2,3) 1) https://arxiv.org/abs/2305.00050.pdf 2) https://arxiv.org/pdf/1905.13211.pdf 3) https://arxiv.org/pdf/2203.15544.pdf&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2305.00050/"&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>Causal Reasoning and Large Language Models: Opening a New Frontier for Causality — mentioned by famouswaffles</title><link>https://news.ycombinator.com/item?id=36037440</link><guid isPermaLink="false">urn:hackerpapers:mention:2305.00050:36037440</guid><pubDate>Mon, 22 May 2023 22:23:07 GMT</pubDate><description>&lt;p&gt;&amp;gt;It&amp;#x27;s not better at reasoning. It&amp;#x27;s barely even capable of it You are wrong. and there&amp;#x27;s many papers to show otherwise. Algorithmic, Casual, Inference, Analogical LLMs reason just fine https://arxiv.org/abs/2212.09196 https://arxiv.org/abs/2305.00050 https://arxiv.org/abs/2204.02329 https://arxiv.org/abs/2211.09066&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2305.00050/"&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>Causal Reasoning and Large Language Models: Opening a New Frontier for Causality — mentioned by famouswaffles</title><link>https://news.ycombinator.com/item?id=36017579</link><guid isPermaLink="false">urn:hackerpapers:mention:2305.00050:36017579</guid><pubDate>Sun, 21 May 2023 02:46:45 GMT</pubDate><description>&lt;p&gt;No world model ? A world model is so obvious papers like these are more confirmation than surprise https://arxiv.org/abs/2305.11169 https://arxiv.org/abs/2210.13382 There a certain sentiment that AGI however you wish to define it won&amp;#x27;t infact be a &amp;quot;We&amp;#x27;ll know it when we see it&amp;quot; situation but rather a &amp;quot;AGI will arrive long before consensus reaches its AGI&amp;quot;. LLMs have made me believe this will 100% be the case, either way. It&amp;#x27;s one thing to argue over things we can&amp;#x27;t evaluate even now but man the 100th &amp;quot;They can&amp;#x27;t reason!&amp;quot; every week is pretty funny when you can basically take your pick of…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2305.00050/"&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>Causal Reasoning and Large Language Models: Opening a New Frontier for Causality — mentioned by famouswaffles</title><link>https://news.ycombinator.com/item?id=35869022</link><guid isPermaLink="false">urn:hackerpapers:mention:2305.00050:35869022</guid><pubDate>Tue, 09 May 2023 01:03:35 GMT</pubDate><description>&lt;p&gt;LLMs are not very bad at reasoning. People say this but struggle to demonstrate how. There are many types of reasoning. For some like abstract analogical reasoning, LLMs are top % performers. https://arxiv.org/abs/2212.09196 There&amp;#x27;s many papers at this point demonstrating pretty strong reasoning. From Casual Reasoning, and explanatory reasoning to algorithmic reasoning. https://arxiv.org/abs/2305.00050 https://arxiv.org/abs/2204.02329 https://arxiv.org/abs/2211.09066 The only kind of reasoning that&amp;#x27;s somewhat lacking is logical reasoning. And even then it&amp;#x27;s not awful, just lagging behind…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2305.00050/"&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>Causal Reasoning and Large Language Models: Opening a New Frontier for Causality — HN submission</title><link>https://news.ycombinator.com/item?id=35788181</link><guid isPermaLink="false">urn:hackerpapers:submission:2305.00050:35788181</guid><pubDate>Tue, 02 May 2023 14:39:26 GMT</pubDate><description>&lt;p&gt;Causal Reasoning and Large Language Models: Opening a New Frontier for Causality&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;5 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2305.00050/"&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>
