Фото: Наталья Селиверстова / РИА Новости
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.
，更多细节参见旺商聊官方下载
Published by matejlou。关于这个话题，Safew下载提供了深入分析
63-летняя Деми Мур вышла в свет с неожиданной стрижкой17:54
他还以一组数据，强调了这门事业的潜力：中国汽车保有量已超过美国，但美国拥有1300万艘游艇，中国仅约12000艘，发展空间巨大。