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作 者:骆林娜 陈佳璇[3] LUO Linna;CHEN Jiaxuan(School of International Chinese Studies,East China Normal University,Shanghai 200062;International Education College,Shanghai University of Traditional Chinese Medicine,Shanghai 201203;School of Literature and Journalism,Hanshan Normal University,Chaozhou,Guangdong 521041)
机构地区:[1]华东师范大学国际汉语文化学院,上海200062 [2]上海中医药大学国际教育学院,上海201203 [3]韩山师范学院文学与新闻传播学院,广东潮州521041
出 处:《文化艺术研究》2025年第2期56-69,114,共15页Studies in Culture and Art
摘 要:在人工智能技术迅速发展的背景下,大语言模型在知识传播与跨文化交流研究中的应用价值日益凸显,但也暴露出种种问题。从“新言语行为分析”出发,以中医药文化的全球传播研究为题,以DeepSeek为对象,考察主体、意图、语境、语篇等因素对人机对话的影响,发现在人机对话的“询问”中合理设置提示语,可以降低大语言模型的幻觉,提高回答的可靠性和学术价值。进一步提出角色设定、分步提问、交叉验证等优化策略,可增强研究结论的准确性。在此基础上,利用优化后的交互方法,可以对中医药文化全球传播的现状、传播路径及受众接受度等展开实证研究,研究结果显示,依靠大语言模型,并不容易直接建立关于中医药的“事实性结构”,却便于把握全球公众对中医药文化的“认知性结构”,这对于研究中医药文化的传播无疑很有意义。真正改变中医药文化的全球传播,固然可以继续借助大语言模型的提示,但真正创造性的方法设计目前依然难以借助大语言模型。Large language models(LLMs)have shown growing value in knowledge dissemination and cross-cultural communication,while also revealing various challenges.This study,based on the framework of new speech act analysis and using the global communication of traditional Chinese medicine as its focus,investigates the influence of factors such as agent,intention,context,and discourse on human–machine dialogues,with DeepSeek as the subject of analysis.The findings suggest that appropriately setting prompts during human–machine interaction can reduce hallucinations and enhance the reliability and academic value of their responses.Furthermore,strategies such as role setting,step-by-step questioning,and cross-verification are proposed to improve accuracy.The study applies optimized interaction methods to explore the situation,paths,and reception of traditional Chinese medicine in the global context.The results show that while LLMs may not easily construct factual structures regarding traditional Chinese medicine,they are effective in capturing its global cognitive structures.Although LLMs can aid the global dissemination of traditional Chinese medicine,creative methodological design still largely remains beyond their current capabilities.
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