我的青少年时代在黄土高原腹地甘肃省定西市安乐村度过。每逢暑假，我和哥哥总会在外婆家住几天。外婆家不远处那片被庄稼层层环绕的黄土山，是我最熟悉的风景。我们经常踩着田埂间没膝的狗尾巴草与蒲公英，深一脚浅一脚地攀爬。那时的我还不知道，这片承载童年欢声笑语的“土山”，是第四次全国文物普查中新发现的北宋故城遗址——张川城遗址。这15到20厘米厚、层层叠叠的夯土层里，竟藏着古人筑城戍边的智慧。那些与庄稼共生的黑釉、褐釉陶瓷片，曾是北宋先民碗碟中的烟火生活，沉淀着上千年的光阴。
"It is well known that big, incriminating stuff has been redacted from what Pam Bondi released," says Stephen Colbert in the Late Show clip above. "And yesterday we got confirmation that the DOJ has withheld or taken down more than 50 pages of material from the Epstein files related to Donald Trump. And it's totally on brand for the DOJ — this DOJ especially — to be protecting Trump. It's the least surprising headline since 'Youngest Child Becomes Theatre Major'."
，这一点在爱思助手下载最新版本中也有详细论述
maintaining account sums, and document processing machines communicating with
「我們以前每個月會外出吃兩次飯，」住在伊朗第二大城市伊斯法罕（Isfahan）的瑪爾珍（Marjan） 說，「現在我們根本不能去了。我們必須把那筆錢省下來付房租。」
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.