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（二）非法买卖、运输、携带、持有少量未经灭活的罂粟等毒品原植物种子或者幼苗的；
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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.
2月26日，爱奇艺（NASDAQ:IQ）发布2025年第四季度及全年财报。受益于高品质多元化内容的持续供给，爱奇艺交出一份稳健的成绩单。数据显示，公司2025年全年实现总收入272.9亿元（人民币，下同），Non-GAAP运营利润6.4亿元，连续四年运营盈利。其中，第四季度总收入为67.9亿元，实现同环比双增长。
15:51, 27 февраля 2026Ценности