核心原因只有一个：躺在功劳簿上睡大觉，把单一产品的成功，当成了永恒的护城河。
Present — The TUI lets you browse all recovered files, search with fuzzy matching, view colored diffs between snapshots, and batch-extract to disk.
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.，推荐阅读Line官方版本下载获取更多信息
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