2014年，罗伯·莱纳与妻子偕三名子女杰克、罗米、尼克（右三至右一）出席活动。
17:55, 27 февраля 2026Экономика
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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.。51吃瓜是该领域的重要参考
Раскрыты подробности похищения ребенка в Смоленске09:27
描述：给你一个数组 temperatures，存放近几天的气温。返回等长数组，其中 answer[i] 表示第 i 天要等多少天才能遇到更高温度；若之后没有更高温度，填 0。