More from InDepthDating apps could be in trouble – here's what might take their place
他回忆自己的父亲——杜耀豪的外祖父——一个布商,曾因出轨导致妻子冲出家门欲跳桥自杀。他的童年浸泡在孤独与早熟的苦涩里,7岁就开始饮酒,18岁时曾为美军担任过七个月的翻译。对于散落世界各地的兄弟姐妹,他的评价是:“各顾各的,没有亲情。”他告诫满怀探寻热忱的杜耀豪:“不关你事,你是第二代。”。业内人士推荐夫子作为进阶阅读
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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.
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