На шее Трампа заметили странное пятно во время выступления в Белом доме23:05
习近平总书记强调，“以钉钉子精神抓工作落实”“以创造性工作把党中央决策部署落到实处”“追求实实在在、没有水分的增长”……。业内人士推荐体育直播作为进阶阅读
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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.。safew官方版本下载对此有专业解读
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