人工智能驱动的学术论文检测框架  

Artificial intelligence driven academic paper detection framework

作　　者：洪宇轩 HONG Yuxuan(The College of Information,Mechanical and Electrical Engineering,Shanghai Normal University,Shanghai 201418,China)

机构地区：[1]上海师范大学信息与机电工程学院,上海201418

出　　处：《计算机应用文摘》2025年第1期105-108,共4页

基　　金：上海师范大学学生科研项目(24LKY137)。

摘　　要：生物医学领域学术论文的质量直接关系到科研成果的传播与应用,确保论文的准确性和可靠性至关重要。随着学术出版的全球化发展,不当语义表达和学术不端行为日益增多,对学术严谨性以及国家形象造成了严重影响。为此,提出了一种基于大模型的语义表达检测框架,可结合自然语言处理与数字签名技术,提升学术论文的质量与安全性。实验结果初步验证了该方法在识别不当语义表达和学术不端行为方面的有效性,同时确保了论文内容的完整性和真实性。The quality of academic papers in the biomedical field is directly related to the dissemination and application of scientific research results,and ensuring the accuracy and reliability of papers is crucial.With the globalization of academic publishing,inappropriate semantic expressions and academic misconduct are increasing,which have a serious impact on academic rigor and national image.Therefore,a semantic expression detection framework based on large models is proposed,which combines natural language processing and digital signature technology to improve the quality and security of academic papers.The experimental results preliminarily verified the effectiveness of this method in identifying inappropriate semantic expressions and academic misconduct,while ensuring the completeness and authenticity of the paper content.

关 键 词：语义表达检测 自然语言处理 检索增强生成技术 大语言模型 图像识别 数字签名技术 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]