How Linguistics Learned to Stop Worrying and Love the Language Models.

IF 13.7 1区 心理学 Q1 BEHAVIORAL SCIENCES
Richard Futrell, Kyle Mahowald
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引用次数: 0

Abstract

Language models can produce fluent, grammatical text. Nonetheless, some maintain that language models don't really learn language and also that, even if they did, that would not be informative for the study of human learning and processing. On the other side, there have been claims that the success of LMs obviates the need for studying linguistic theory and structure. We argue that both extremes are wrong. LMs can contribute to fundamental questions about linguistic structure, language processing, and learning. They force us to rethink arguments and ways of thinking that have been foundational in linguistics. While they do not replace linguistic structure and theory, they serve as model systems and working proofs of concept for gradient, usage-based approaches to language. We offer an optimistic take on the relationship between language models and linguistics.

语言学如何学会停止担忧并热爱语言模型。
语言模型可以产生流畅的、合乎语法的文本。尽管如此,一些人坚持认为语言模型并不能真正学习语言,而且,即使它们真的学习了语言,也不能为研究人类的学习和处理提供信息。另一方面,有人声称LMs的成功消除了研究语言理论和结构的需要。我们认为这两个极端都是错误的。LMs可以对语言结构、语言处理和学习等基本问题做出贡献。它们迫使我们重新思考作为语言学基础的论点和思维方式。虽然它们不能取代语言结构和理论,但它们可以作为模型系统和概念的有效证明,用于梯度,基于使用的语言方法。我们对语言模型和语言学之间的关系提出了乐观的看法。
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来源期刊
Behavioral and Brain Sciences
Behavioral and Brain Sciences 医学-行为科学
CiteScore
1.40
自引率
1.70%
发文量
353
期刊介绍: Behavioral and Brain Sciences (BBS) is a highly respected journal that employs an innovative approach called Open Peer Commentary. This format allows for the publication of noteworthy and contentious research from various fields including psychology, neuroscience, behavioral biology, and cognitive science. Each article is accompanied by 20-40 commentaries from experts across these disciplines, as well as a response from the author themselves. This unique setup creates a captivating forum for the exchange of ideas, critical analysis, and the integration of research within the behavioral and brain sciences, spanning topics from molecular neurobiology and artificial intelligence to the philosophy of the mind.
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