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.
Ранее врач-психиатр, нарколог Руслан Исаев предупредил, что риск алкоголизма выше у людей с психическими расстройствами. По его словам, спиртное помогает им на время заглушить симптомы основного заболевания, но в перспективе ухудшает состояние.
。safew官方版本下载对此有专业解读
Felo.ai令人意外的是，Felo 不支持 Markdown 文档上传，毕竟 Markdown 是 AI 大模型的通用「语言」。因此测评中我改用了博客原文链接。。safew官方下载对此有专业解读
2024年12月24日 星期二 新京报，详情可参考爱思助手下载最新版本