The Mouse Cancer Cell line Atlas (MCCA) provides major advances towards a mechanistic understanding of cancer genomes.
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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郭鳳儀是34名被香港警方國安處通緝的異見人士之一。她被指參與2019年的大規模民主示威，其後涉嫌勾結外國勢力及違反《香港國安法》。，推荐阅读下载安装 谷歌浏览器 开启极速安全的 上网之旅。获取更多信息