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Последние новости，更多细节参见safew官方版本下载
There's lots of Moon on display tonight, so plenty of opportunity to do some Moon gazing. With just your naked eye, you'll be able to see the Mares Tranquillitatis, Vaporum and Serenitatis. With binoculars you'll also be able to see the Mare Nectaris, and the Alphonsus and Endymion Craters, and with a telescope you'll see also see he Apollo 16 and 11 landing spots, and the Rupes Altai.，更多细节参见Line官方版本下载
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.
Watch: Astronauts return to Earth after extended stay in Space