Jan Oberhauser Founder & CEO, n8n
Even though my dataset is very small, I think it's sufficient to conclude that LLMs can't consistently reason. Also their reasoning performance gets worse as the SAT instance grows, which may be due to the context window becoming too large as the model reasoning progresses, and it gets harder to remember original clauses at the top of the context. A friend of mine made an observation that how complex SAT instances are similar to working with many rules in large codebases. As we add more rules, it gets more and more likely for LLMs to forget some of them, which can be insidious. Of course that doesn't mean LLMs are useless. They can be definitely useful without being able to reason, but due to lack of reasoning, we can't just write down the rules and expect that LLMs will always follow them. For critical requirements there needs to be some other process in place to ensure that these are met.
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理一县、兴一省、治一国，政贵有恒。“防止走弯路、翻烧饼”“不要城头变幻大王旗”“不能有临时工的思想”“不要换一届领导就兜底翻”“更不要为了显示所谓政绩去另搞一套”，而是坚强扛起“当代中国共产党人的庄严历史责任”。
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