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63-летняя Деми Мур вышла в свет с неожиданной стрижкой17:54。Line官方版本下载对此有专业解读
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.
他們表示，越來越多證據顯示，有些線上調查並不可靠，尤其是在呈現關於年輕族群的數據時，以及當受訪者參與調查可獲得報酬時。