对话代理与人类语言的理解：对人工智能、大语言模型和认知科学的反思
Conversational Agents and the Understanding of Human Language: Reflections on AI, LLMs, and Cognitive Science
AI总结：
本文探讨计算机自然语言处理与人类语言能力理解的关系，分析NLP发展与语言能力理论的异同，指出语言技术的进步未显著深化人类语言处理机制的理解。
摘要：
本文讨论计算机自然语言处理（NLP）与语言学和认知科学研究中人类语言能力理解之间的关系。我们概述了NLP从起源到大语言模型时代的演变，并突出各主要范式与人类语言能力理论的相似性和差异性。我们得出结论，尽管当前基于人工神经网络的聊天机器人展现出令人印象深刻的语言能力，但语言技术的发展并未显著加深我们对人类大脑如何处理自然语言的理解。
英文摘要：
In this paper, we discuss the relationship between natural language processing by computers (NLP) and the understanding of the human language capacity, as studied by linguistics and cognitive science. We outline the evolution of NLP from its beginnings until the age of large language models, and highlight for each of its main paradigms some similarities and differences with theories of the human language capacity. We conclude that the evolution of language technology has not substantially deepened our understanding of how human minds process natural language, despite the impressive language abilities attained by current chatbots using artificial neural networks.
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。
