2. Separate same-font from cross-font scoring. Same-font comparisons (mean 0.536) are the strongest signal. A namespace validation system that weights same-font scores higher than cross-font scores will have better precision than one that treats all fonts equally.
I wanted to test this claim with SAT problems. Why SAT? Because solving SAT problems require applying very few rules consistently. The principle stays the same even if you have millions of variables or just a couple. So if you know how to reason properly any SAT instances is solvable given enough time. Also, it's easy to generate completely random SAT problems that make it less likely for LLM to solve the problem based on pure pattern recognition. Therefore, I think it is a good problem type to test whether LLMs can generalize basic rules beyond their training data.,推荐阅读91视频获取更多信息
,这一点在Line官方版本下载中也有详细论述
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