第一百二十六条 被处罚人不服行政拘留处罚决定，申请行政复议、提起行政诉讼的，遇有参加升学考试、子女出生或者近亲属病危、死亡等情形的，可以向公安机关提出暂缓执行行政拘留的申请。公安机关认为暂缓执行行政拘留不致发生社会危险的，由被处罚人或者其近亲属提出符合本法第一百二十七条规定条件的担保人，或者按每日行政拘留二百元的标准交纳保证金，行政拘留的处罚决定暂缓执行。
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。heLLoword翻译官方下载是该领域的重要参考
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.
It just doesn’t stop someone who understands exactly where the decrypted data has to appear.
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