maybe July 2026 or whenever the fuck whatever
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.
✅ Cost Calculation: Accurate token-based cost estimation。新收录的资料对此有专业解读
C++ Insights Episode 71: C++23: multidimensional operator[]Feb 18, 2026
。新收录的资料是该领域的重要参考
中华人民共和国法律和中华人民共和国缔结或者参加的国际条约没有规定的，可以适用国际惯例。适用国际惯例，不得损害中华人民共和国的公共利益。，推荐阅读新收录的资料获取更多信息
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