大模型在垂直领域应用的现状与挑战

doi:10.3778/j.issn.1002-8331.2409-0181

摘要/Abstract

摘要： 近年来，以ChatGPT为代表的大语言模型在多个领域受到广泛的关注，并取得优异的表现，推动了人工智能技术的新一轮发展浪潮。目前国产大模型数量已有上百个，覆盖多个行业领域，应用场景也不断扩展。为了更好地应对大模型在自然语言处理中的发展及其对通用任务和领域应用带来的冲击，对自然语言处理和大模型的发展历程进行回顾，阐述了当前大模型的相关技术以及大模型在医疗、法律、金融等垂直领域的应用，并对大模型在应用过程中面临的挑战如能力缺陷、协同问题等作出分析。最后，针对这些问题探讨了大模型在实际应用中的未来研究方向。

关键词: 自然语言处理, 人工智能, 大语言模型, 垂直领域

Abstract: In recent years, large language models, exemplified by ChatGPT, have garnered significant attention across various fields and demonstrated outstanding performance, fueling a new wave of advancements in artificial intelligence technology. At present, there are over a hundred domestic large language models, spanning multiple industry sectors, with their applications continuously expanding. To better address the development of large language models in natural language processing and their impact on both general tasks and specialized domain applications, this paper reviews the evolution of natural language processing and large language models. It provides an overview of current large model technologies and their applications in vertical domains such as healthcare, law, and finance. Furthermore, it analyzes the challenges faced by large models during deployment, such as limitations in capabilities and collaboration difficulties. Lastly, the paper discusses the future research directions aimed at addressing these issues and enhancing the practical application of large language models.

Key words: natural language processing, artificial intelligence, large language models, vertical domains

籍欣萌, 昝红英, 崔婷婷, 张坤丽. 大模型在垂直领域应用的现状与挑战[J]. 计算机工程与应用, 2025, 61(12): 1-11.

JI Xinmeng, ZAN Hongying, CUI Tingting, ZHANG Kunli. Status and Challenges of Large Language Models Applications in Vertical Domains[J]. Computer Engineering and Applications, 2025, 61(12): 1-11.

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