20版 - 让九色鹿替我们“扯一把地气”(书里书外)

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第二十一条 核燃料循环设施建设项目由国务院核工业主管部门依法审批或者核准,重大项目报国务院审批或者核准。申请条件、审批程序和时限等按照国家规定执行。

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.

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Thomas Knoll’s Algorithm