「如果你不知道對方的意識型態或立場，而引起他不愉快的話，你自己也不會很舒服。尤其他還是你重視的朋友的話。」
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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For US energy companies, however, there are huge practical difficulties to be overcome. Venezuela's state-owned oil company, PDVSA, is a shadow of its former self.
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До этого синоптик рассказала, что мощных снегопадов в Москве на мартовские праздники ждать не стоит.
Овечкин продлил безголевую серию в составе Вашингтона09:40。Line官方版本下载是该领域的重要参考