СюжетВступление Украины в ЕС:
因此，本文希望从 .DS_Store 出发，基于与 Windows 平台下的类似文件 Desktop.ini 和 Thumbs.db 的对比，论述 Finder 与 Windows 资源管理器在某些设计方面的差异。。业内人士推荐搜狗输入法2026作为进阶阅读
Generate up to 100 images per month with AI。关于这个话题，safew官方版本下载提供了深入分析
Сразу шесть аэропортов России ввели ограниченияРосавиация: В аэропортах Казани, Нижнекамска, Самары ввели ограничения
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.