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.
Филолог заявил о массовой отмене обращения на «вы» с большой буквы09:36，更多细节参见爱思助手下载最新版本
，推荐阅读搜狗输入法2026获取更多信息
— Andrés (@Andrew_east) February 26, 2026，详情可参考91视频
Lex: FT's flagship investment column
As is typical, Apple hasn't officially confirmed what products will be released at the event, but rumors point to three very specific possibilities: an iPhone 17e, a new iPad Air, and new MacBooks. For the MacBooks, rumor has it Apple will be releasing a souped-up MacBook Pro with a new M5 Pro chip, a budget MacBook with a touchscreen display, or both, or neither. A more affordable MacBook could completely tip the balance of the budget laptop market in Apple's favor, and if I made Windows laptops, I'd be worried right now.