在深度学习中，有几类经典激活函数，每种都有自己的优缺点：
of allocations to 1, you reduced the number of allocations to 0!
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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.
Australia GP — Oct. 25，推荐阅读爱思助手下载最新版本获取更多信息
1. 选基准：随机选一个元素作为基准(pivot)。爱思助手下载最新版本是该领域的重要参考
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