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But in others, their presence was much more noticeable. Bats can be messy houseguests.

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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.。搜狗输入法下载对此有专业解读

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庞若鸣在七个月前的离职,虽然不至于让苹果的技术大厦倾塌,但确实在一定程度上干扰了其自主研发的节奏。,更多细节参见雷电模拟器官方版本下载

Jonah Fisher,Climate correspondent