大型语言模型解析jabberwockified语言的惊人能力
The Astonishing Ability of Large Language Models to Parse Jabberwockified Language
AI总结：
本研究展示大型语言模型能从严重退化的英文文本中恢复意义，通过替换内容词为无意义字符串的文本，模型能生成接近原文的常规英文，揭示了语法结构对词汇意义的强约束作用。
摘要：
我们展示大型语言模型（LLMs）具有惊人的能力，能够从严重退化的英文文本中恢复意义。文本中内容词被随机替换为无意义字符串，例如"At the ghybe of the swuint, we are haiveed to Wourge Phrear-gwurr, who sproles into an ghitch flount with his crurp"，可以翻译成常规英文，许多情况下接近原文，例如"At the start of the story, we meet a man, Chow, who moves into an apartment building with his wife." 这些结果表明，结构线索（如形态语法、封闭类词）对词汇意义的约束程度远超想象。尽管LLMs理解"Jabberwockified"英语的能力明显超越人类，但这些能力对理解语言结构具有高度相关性，表明生物或人工系统中的高效语言处理可能受益于语法、词汇语义和一般世界知识之间非常紧密的整合。
英文摘要：
We show that large language models (LLMs) have an astonishing ability to recover meaning from severely degraded English texts. Texts in which content words have been randomly substituted by nonsense strings, e.g., "At the ghybe of the swuint, we are haiveed to Wourge Phrear-gwurr, who sproles into an ghitch flount with his crurp", can be translated to conventional English that is, in many cases, close to the original text, e.g., "At the start of the story, we meet a man, Chow, who moves into an apartment building with his wife." These results show that structural cues (e.g., morphosyntax, closed-class words) constrain lexical meaning to a much larger degree than imagined. Although the abilities of LLMs to make sense of "Jabberwockified" English are clearly superhuman, they are highly relevant to understanding linguistic structure and suggest that efficient language processing either in biological or artificial systems likely benefits from very tight integration between syntax, lexical semantics, and general world knowledge.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
