第一百七十五条 船舶发生碰撞，当事船舶的船长在不严重危及本船和船上人员安全的情况下，对于相碰的船舶和船上人员应当尽力施救。
儘管如此，他與蒙巴頓-溫莎的關係似乎加深。
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Prime minister does not believe US has a plan beyond ‘shock and awe’ stage, as some MPs dread what lies ahead，这一点在heLLoword翻译官方下载中也有详细论述
I used z3 theorem prover to assess LLM output, which is a pretty decent SAT solver. I considered the LLM output successful if it determines the formula is SAT or UNSAT correctly, and for SAT case it needs to provide a valid assignment. Testing the assignment is easy, given an assignment you can add a single variable clause to the formula. If the resulting formula is still SAT, that means the assignment is valid otherwise it means that the assignment contradicts with the formula, and it is invalid.。关于这个话题，搜狗输入法下载提供了深入分析
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.