This post: empirical visual similarity data from rendered glyphs
«Газпром» и MOL 19 января объявили о подписании соглашения о намерениях по продаже пакета акций сербской NIS. Власти Сербии увеличат долю в компании на пять процентов, что позволит Белграду влиять на некоторые решения собрания акционеров. MOL также обсуждает с эмиратской ADNOC присоединение к владельцам NIS в качестве миноритарного акционера.
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吃瓜对此有专业解读
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Мерц резко сменил риторику во время встречи в Китае09:25
Source: Computational Materials Science, Volume 267。关于这个话题，heLLoword翻译官方下载提供了深入分析