证明生成式AI与生成语言学兼容，且能相互促进。
On the Compatibility of Generative AI and Generative Linguistics
- 将语言模型视为形式化生成模型，呼应乔姆斯基理论初衷。
- 语言模型可辅助发现句法生成规则，推动语法研究。
- 为语言习得和通用语法研究提供新工具，适合语言学与AI交叉研究者。
20世纪中叶，语言学家诺姆·乔姆斯基创立了生成语言学，通过构建语言的计算与哲学基础，将语言定义为人类心智或人工机器中的形式系统，推动了符号人工智能的研究。近年来，以神经语言模型为代表的非符号人工智能展现出卓越的语言性能，引发对传统方法的质疑，也促使人们思考生成式AI与生成语言学的兼容性。本文主张二者不仅兼容，且在三个层面相互强化：首先，语言模型本质上是乔姆斯基形式语言理论所设想的形式生成模型；其次，语言模型有助于实现乔姆斯基《句法结构》中提出的发现程序；第三，语言模型可成为其最小化原则与普遍语法研究的重要助力。反过来，生成语言学也为评估和改进语言模型及其他生成式计算模型提供了理论基础。
原文摘要 · Abstract (English)
In mid-20th century, the linguist Noam Chomsky established generative linguistics, and made significant contributions to linguistics, computer science, and cognitive science by developing the computational and philosophical foundations for a theory that defined language as a formal system, instantiated in human minds or artificial machines. These developments in turn ushered a wave of research on symbolic Artificial Intelligence (AI). More recently, a new wave of non-symbolic AI has emerged with neural Language Models (LMs) that exhibit impressive linguistic performance, leading many to question the older approach and wonder about the the compatibility of generative AI and generative linguistics. In this paper, we argue that generative AI is compatible with generative linguistics and reinforces its basic tenets in at least three ways. First, we argue that LMs are formal generative models as intended originally in Chomsky's work on formal language theory. Second, LMs can help develop a program for discovery procedures as defined by Chomsky's "Syntactic Structures". Third, LMs can be a major asset for Chomsky's minimalist approach to Universal Grammar and language acquisition. In turn, generative linguistics can provide the foundation for evaluating and improving LMs as well as other generative computational models of language.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。