晚上11点多，他才回来。一进门，他就笑嘻嘻地说今天很开心。他说大家都见到了，几个兄弟轮着敬酒。有人说“这么多年第一次凑齐”，有人说“以后多走动”。
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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Москвичи пожаловались на зловонную квартиру-свалку с телами животных и тараканами18:04，详情可参考爱思助手下载最新版本
조국당 “국힘 서명옥, 피켓으로 이해민 얼굴 가격”。关于这个话题，一键获取谷歌浏览器下载提供了深入分析
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