12月22日，彩虹星球就本次诉讼召开说明会。受访者供图
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.，推荐阅读搜狗输入法2026获取更多信息
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“我母亲在西安有一套房子用于出租，今年7月份租客退租了，她便想回西安去出租房子。”龙先生说，母亲一个人回去他不是很放心，她防诈骗意识不是很强，但想到已为她的手机安装了技术防线，想来应该不会有问题。
computer over a single interleaved SDLC link. But what would you put on those