Tributes paid to ‘very loving and caring’ British hiker killed in Nepal bus crash

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第三十七条 爆炸性、毒害性、放射性、腐蚀性物质或者传染病病原体等危险物质被盗、被抢或者丢失,未按规定报告的,处五日以下拘留;故意隐瞒不报的,处五日以上十日以下拘留。

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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.