This viral animation, which began circulating widely in 2016, shows Dragonite and Charizard dancing with surprising elegance, their massive bodies moving with pop-star precision. Most people know it set to Ariana Grande's "Into You," where the contrast between her breathless vocals and their enthusiastic choreography made the clip instantly funny and weirdly perfect.
Офтальмолог дал советы по настройке монитора для защиты глазОкулист Азнаурян: Блики на экране от света увеличивают нагрузку на глаза，更多细节参见同城约会
* @returns {number[]} 每个位置需等待的天数（无更高温则为0），更多细节参见搜狗输入法2026
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.