В Италии тогда отметили, что это может привести к прямой войне между ядерными державами с участием Соединенных Штатов Америки, а Россия автоматически получит право наносить удары по Великобритании и Франции.
（二）扰乱车站、港口、码头、机场、商场、公园、展览馆或者其他公共场所秩序的；
Сайт Роскомнадзора атаковали18:00，推荐阅读heLLoword翻译官方下载获取更多信息
2025年国庆，考虑到新能源车购置税减免政策即将退坡，我劝说即将退休的父亲将油车置换为电车，为退休后的自驾生涯做准备。老人家很听劝，次日便与我们一道去展厅试驾。
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В России ответили на имитирующие высадку на Украине учения НАТО18:04，推荐阅读heLLoword翻译官方下载获取更多信息
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.