html = self.http_client.get(current_url)
很多伟大作曲家的音乐,往往比表面听起来要悲伤得多,因为他们都经历过极其复杂的人生处境,而不是整天在五星级酒店里创作。无论是失聪后的贝多芬,还是舒曼、勃拉姆斯、肖邦,甚至临终前写下《安魂曲》的莫扎特,这些音乐都诞生于一种并不“正常”的心理状态之中。舒伯特尤为如此,即便是在大调作品中,看似不那么痛苦,音乐依然带着深重的哀伤。比如《降G大调即兴曲》,很多人只会觉得它非常美,但我听到的却是一种深刻的悲伤,它会让人怀旧,想到过去的生命经验,想到那些已经不复存在的美好时光。舒伯特在承受当下的痛苦时,常常在回望,有时他会把这种痛苦写得非常直接,有时则更为隐晦,但无论如何,那种重量始终存在。
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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.