思路：倒序遍历 + 单调索引栈（仅存索引），计算下一个高温的间隔天数。栈顶索引 - 当前索引即为等待天数。
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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但从结果来看，这种收缩反而直接导致了声量断崖式下跌。在新品牌与新产品层出不穷的美妆赛道，没有声音比有负面声音更可怕。
。safew官方版本下载是该领域的重要参考
Science & Environment。关于这个话题，同城约会提供了深入分析
Prime Video hosts more exciting NBA action today, with the Minnesota Timberwolves visiting the LA Clippers for a Western Conference showdown. The Timberwolves have a stronger regular season record, going 21-17 in conference games versus the Clippers' 17-17.