We report on an astonishing ability of large language models (LLMs) to make sense of "Jabberwocky" language in which most or all content words have been randomly replaced by nonsense strings, e.g., translating "He dwushed a ghanc zawk" to "He dragged a spare chair". This result addresses ongoing controversies regarding how to best think of what LLMs are doing: are they a language mimic, a database, a blurry version of the Web? The ability of LLMs to recover meaning from structural patterns speaks to the unreasonable effectiveness of pattern-matching. Pattern-matching is not an alternative to "real" intelligence, but rather a key ingredient.

翻译：我们报告了大型语言模型（LLMs）在理解“胡言乱语”语言方面令人惊讶的能力——这类语言中大部分或全部实词均被随机替换为无意义字符串，例如将“He dwushed a ghanc zawk”翻译为“He dragged a spare chair”。这一发现回应了当前关于如何理解LLMs本质的争议：它们究竟是语言模仿者、数据库，还是模糊化的网络版本？LLMs从结构模式中恢复意义的能力，揭示了模式匹配的不合理有效性。模式匹配并非“真正”智能的替代品，而是其关键组成部分。