The president initially invited the women late Sunday, when he called to congratulate the men for their 2-1 overtime win over Canada. The women’s team was still in Milan, three days after also beating Canada 2-1 in overtime.
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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Мощный удар Израиля по Ирану попал на видео09:41
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// 逻辑：这些数比当前元素小/相等，不可能成为「左侧元素的下一个更大值」，直接移除。关于这个话题，搜狗输入法2026提供了深入分析
This behavioral shift creates a new visibility challenge. Your content might rank perfectly on Google, but if it's invisible to AI models when they're formulating answers, you're missing an enormous and growing segment of potential traffic. The users who discover information through AI tools never even see your traditional search rankings because they never visit a search results page.