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.
'We have a new major number purely because I'm easily confused and not good with big numbers' says Linus Torvalds about Linux 7.0
，这一点在雷电模拟器官方版本下载中也有详细论述
正是基于需求扩容的预期、政策逐步松动、制造能力已然成熟三个因素，刘强东选择果断入场。，这一点在旺商聊官方下载中也有详细论述
Beckham's girlfriend Jackie Apostel and his dad's old team-mate Gary Neville were in the crowd，详情可参考Line官方版本下载
Ранее сообщалось, что в период с декабря 2019 года по июль 2024-го подсудимые организовали незаконную схему стимулирующих выплат сотрудникам вуза. Все деньги они присваивали себе. В преступную схему были вовлечены 20 сотрудников БФУ. Общая сумма причиненного ущерба составила 35,1 миллиона рублей.