Large Language Models and Applications: The Rebirth of Enterprise Knowledge Management and the Rise of Prompt Libraries

被引:2
|
作者
O'Leary, Daniel E. [1 ]
机构
[1] Univ Southern Calif, Marshall Sch Business, Los Angeles, CA 90089 USA
关键词
Knowledge management; Cognition; Intelligent systems; Large language models; Enterprise resource planning; Libraries;
D O I
10.1109/MIS.2024.3366648
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article investigates how large language systems and the apps developed for them provide a platform for enterprise knowledge management. For those resulting systems to provide consistent and accurate responses for knowledge management, enterprises are using different approaches in their prompts, such as few-shot learning, specification of purpose, and chain-of-thought reasoning. As better and more successful prompts are being built, they are being captured and prompt libraries are being created.
引用
收藏
页码:72 / 75
页数:4
相关论文
共 50 条
  • [31] Navigating the security landscape of large language models in enterprise information systems
    Gupta, Brij B.
    Gaurav, Akshat
    Arya, Varsha
    ENTERPRISE INFORMATION SYSTEMS, 2024, 18 (04)
  • [32] Studies on the Use of Large Language Models for the Automation of Business Processes in Enterprise Resource Planning Systems
    Schnepf, Jonas
    Engin, Tugranur
    Anderer, Simon
    Scheuermann, Bernd
    NATURAL LANGUAGE PROCESSING AND INFORMATION SYSTEMS, PT I, NLDB 2024, 2024, 14762 : 16 - 31
  • [33] A comprehensive analysis of gender, racial, and prompt-induced biases in large language models
    Torres, Nicolas
    Ulloa, Catalina
    Araya, Ignacio
    Ayala, Matias
    Jara, Sebastian
    INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS, 2024,
  • [34] Improving large language models for clinical named entity recognition via prompt engineering
    Hu, Yan
    Chen, Qingyu
    Du, Jingcheng
    Peng, Xueqing
    Keloth, Vipina Kuttichi
    Zuo, Xu
    Zhou, Yujia
    Li, Zehan
    Jiang, Xiaoqian
    Lu, Zhiyong
    Roberts, Kirk
    Xu, Hua
    JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2024, 31 (09) : 1812 - 1820
  • [35] Enhancing user prompt confidentiality in Large Language Models through advanced differential encryption
    Gupta, Brij B.
    Gaurav, Akshat
    Arya, Varsha
    Alhalabi, Wadee
    Alsalman, Dheyaaldin
    Vijayakumar, P.
    COMPUTERS & ELECTRICAL ENGINEERING, 2024, 116
  • [36] Unleashing the Power of Large Language Models for Legal Applications
    Zhang, Dell
    Petrova, Alina
    Trautmann, Dietrich
    Schilder, Frank
    PROCEEDINGS OF THE 32ND ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, CIKM 2023, 2023, : 5257 - 5258
  • [37] Novel applications of large language models in clinical research
    Abers, Michael S.
    Mathias, Rasika A.
    JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY, 2025, 155 (03) : 813 - 814
  • [38] Models of knowledge management of shipbuilding virtual enterprise based on web service
    Wang, Zhiying
    Tang, Hongyu
    International Conference on Management Innovation, Vols 1 and 2, 2007, : 356 - 360
  • [39] Large language models: a survey of their development, capabilities, and applications
    Annepaka, Yadagiri
    Pakray, Partha
    KNOWLEDGE AND INFORMATION SYSTEMS, 2025, 67 (03) : 2967 - 3022
  • [40] Bridging Enterprise Knowledge Management and Natural Language Processing - Integration Framework and a Prototype
    Cappel, Justus
    Chasin, Friedrich
    DESIGN SCIENCE RESEARCH FOR A RESILIENT FUTURE, DESRIST 2024, 2024, 14621 : 278 - 294