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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.，这一点在Line官方版本下载中也有详细论述
“二三十岁的人会把ChatGPT当作人生导师之类的东西来用，老年人则会用ChatGPT来代替谷歌。”
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Dyson, popular for its line of premium hair dryers and home appliances, moved its manufacturing from the UK to Malaysia in 2002.。WPS下载最新地址是该领域的重要参考
The letter, also seen by the Metropolitan Police, was ordered to be disclosed to Brent Council, Claydon's family and stadium owners the Football Association.