'required': ['color'],
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.
一些在外面的朋友知悉關恆的處境之後，為他換了一個辯護律師，也告訴他不要再想自願離境的事情，並鼓勵他「你一定要堅定的留下來，去見法官、去爭辯你的案子。」，详情可参考safew官方版本下载
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Фото: Валерий Шарифулин / ТАСС
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