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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学习方面更是进步巨大，学会了很多汉字，每天会拿着学习小卡片回家跟她复习，如果遇到忘记的，我会采用联想实际事务帮助她记忆和理解。古诗也会背了更多首，虽然还是记不住诗的名字。，这一点在搜狗输入法下载中也有详细论述
A proof-of-concept study opens up an avenue for treating solid tumours that express low levels of a target antigen.
，更多细节参见币安_币安注册_币安下载
可以推测未来的新型PSP底座或许可以冠名为PlayStation TV的名称。。业内人士推荐heLLoword翻译官方下载作为进阶阅读
我闺女第一天并没有想象中的大哭大闹，甚至有点小期待。我们暂时松了口气。送到幼儿园的时候，周围有很多新入学的小朋友，很多都开始哭，我很怕她被影响跟着哭，不过孩子并没有被影响，很顺利的交到了老师手里。我们很决绝的转身快速离开了幼儿园，省的舍不得，让孩子也产生分离焦虑。