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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.,推荐阅读heLLoword翻译官方下载获取更多信息
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European go-to-market search firm Nobel Recruitment has acquired Berlin-based ARRtist, a practitioner-led tech community platform for founders, C-level executives and investors. The deal strengthens Nobel’s position in Germany while expanding its reach beyond executive search into community building and ecosystem development. Financial terms were not disclosed. Founded more than four years ago, ARRtist built a […],这一点在WPS官方版本下载中也有详细论述
In early 2025, baby Amy was born through the first living womb donation in the UK. Her mother received her older sister's womb in a transplant operation in January 2023. Her sister had already had two children of her own.