大语言模型背景下促进大湾区高职科研成果产出的团队合作策略探讨  

Exploration of team collaboration strategies to promote the output of scientific research achievements in higher vocational education in the Greater Bay Area under the background of the Large Language Model

作　　者：徐永冰 张帅 Yongbing Xu;Shuai Zhang(Guangdong South China Vocational College of Industry and Commerce,Guangzhou,Guangdong 510095,China)

机构地区：[1]广东南华工商职业学院,广东广州510095

出　　处：《产业科技创新》2024年第5期28-31,共4页Industrial Technology Innovation

基　　金：广东南华工商职业学院2023年度校级科研项目立项项目“大语言模型背景下团队合作模式对大湾区高职科研成果产出增长的影响(2023Y08)”。

摘　　要：大语言模型为科研团队合作带来新的机遇,但大湾区高职院校在应用该技术推动科研创新时仍面临诸多挑战。本文分析了大语言模型在助力大湾区高职科研团队协同创新方面的优势,剖析了当前存在的跨学科知识融合不足、自然语言处理技术适配性差、人机协同研究范式不成熟、数据安全隐患等问题。针对这些难点,提出了构建跨学科知识图谱、优化技术适配流程、探索人机协同新范式、完善数据安全保护机制等一系列应对策略。本文的研究可为大湾区高职院校深化大语言模型在科研领域的应用提供参考。Large language models bring new opportunities for research team collaboration in scientific research,but higher vocational colleges in the Greater Bay Area still face many challenges in applying this technology to promote research innovation.This paper analyzes the advantages of large language models in supporting collaborative innovation among research teams in Greater Bay Area higher vocational colleges and examines current issues such as insufficient interdisciplinary knowledge integration,poor adaptability of natural language processing technologies,immature human-machine collaboration research paradigms,and data security risks.To address these challenges,strategies are proposed,including the construction of interdisciplinary knowledge graphs,optimization of technology adaptation processes,exploration of new human-machine collaboration paradigms,and improvement of data security mechanisms.This study provides reference for enhancing the application of large language models in the research fields of higher vocational colleges in the Greater Bay Area.

关 键 词：大语言模型 科研团队合作 高职院校 

分 类 号：F299.27[经济管理—国民经济]