用哲学框架解析大模型在语言学中的解释力，提出其介于可能与实际解释之间。
Large Language Models as Modal Models in Linguistics
- 以模态建模理论分析大模型，将其视为语言习得的可能解释工具。
- 当前大模型尚无法满足人类语言实际解释的机制要求。
- 为语言学研究提供评估大模型价值的精准框架，适合语言学与AI交叉研究者。
大型语言模型（LLMs）的快速发展引发了关于其对语言理论意义的争论，主要分为三种立场：绝缘主义认为大模型与人类语言无关；消解主义主张大模型可取代传统语言理论；调和主义则视其为有用的研究工具。本文引入科学哲学中的模态建模框架，论证即使大模型不对应人类认知结构，仍具有真正的认识论价值，可作为最小模型提供‘如何可能’解释（HPEs），用于检验语言习得与语言能力的模态假设。进而探讨大模型成为‘如何实际’解释（HAEs）的条件，基于科学解释的机制论，指出当前大模型尚未满足这些要求。据此，本文提出将大模型的解释力理解为从HPE到HAE的连续谱系，避免过度或低估其作用，为语言科学研究中大模型角色的评估提供更精确的基础。
原文摘要 · Abstract (English)
The rapid advancement of large language models (LLMs) has intensified debates about their significance for linguistic theory. These debates are commonly divided into three positions: insulationism, which regards LLMs as irrelevant to human language; eliminativism, which claims that LLMs can replace traditional linguistic theories; and conciliationism, which views them as useful tools for linguistic research. To clarify these positions, this paper applies the framework of modal modeling from the philosophy of science. We argue that LLMs possess genuine epistemic value as minimal models, even without structural correspondence to human cognition. In particular, they can provide how-possibly explanations (HPEs) by testing modal claims about language acquisition and linguistic competence. We then examine the conditions under which LLMs could qualify as how-actually explanations (HAEs) of human language, drawing on the mechanistic account of scientific explanation. We argue that current LLMs do not yet satisfy these requirements. On the basis of this analysis, we propose understanding the explanatory power of LLMs as lying on a continuum between HPEs and HAEs. This framework avoids both overstating and understating their explanatory significance and offers a more precise basis for evaluating the role of LLMs in the scientific study of language.
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