I love being a parent. The thing I find most fascinating about the experience is how it throws a mirror not just on one’s own childhood, but on all of human nature. It’s an obvious point, but one that I never thought about before having kids: all newborn babies are always the same, everywhere. And then, slowly but surely, they become not the same. As cultural and family influences accumulate like sedimentary layers in these tiny personalities, you can see nurture reshaping nature in a deeply embodied, physical way.
遥遥领先不假，但不够完美也是真的。
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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.