陆逸轩：我不会因为这些经历而改变自己对肖邦的态度。我始终热爱他的音乐，每一次演奏都会有新的发现，也会不断提醒我肖邦为何如此伟大。但在这次比赛结束之后，我确实很想尽快翻过肖赛这一章，不再去想它。现在有太多噪音，互联网和社交媒体让越来越多的人在并不了解实情也没有相关知识的情况下随意发表意见，这些东西对我来说已经变得过于嘈杂，我不想再被它们占据心力。
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.。快连下载安装对此有专业解读
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Pokémon FireRed Version (Nintendo Switch)