Standard Digital
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safew官方下载中也有详细论述
「我們已經告訴媒體我們所知的一切有關克林頓總統與愛潑斯坦旅行的信息,」他說。「事實就是事實，真相就是真相，而且都站在我們這邊。」
A common sentiment expressed by readers is that the language starting from 1200 AD is a foreign and incomprehensible. I am not sure I would agree. While Old English absolutely requires some effort to learn, I think with a little analysis it is much closer to Modern English than we think - and certainly closer to that than it is to say, Modern German.