随着大模型逐渐变成学习、工作中不可或缺的生产力工具，其伴生的问题也日益凸显。AI经常 会"一本正经地胡说八道"，生成看似合理的虚假信息；一些人利用AI工具代写作业甚至毕业论文，极大 冲击着学术诚信和规范；AI生成内容的流畅性和逻辑性越来越强，人类识别困难，但论文AI率检测系 统有待完善，论文被误判的问题时有发生……如何精准识别AI生成内容，成为亟待解决的问题。 南开大学计算机学院媒体计算实验室近日取得的一项研究成果，或为解决这些难题提供可行方案。 该成果创新性地提出直接差异学习（DDL）优化策略，教会AI用"火眼金睛"辨别人机不同，实现AI检 测性能的巨大突破。相关成果论文已被ACM MM 2025（第33届ACM国际多媒体会议）接收。 团队还提出了一个全面的测试基准数据集MIRAGE，该数据集使用13种主流的商用大模型以及4种 先进的开源大模型，生成了接近10万条"人类—AI"文本对。 "MIRAGE是目前唯一聚焦商用大语言模型检测的基准数据集。如果说之前的基准数据集是由少且 能力简单的大模型命题出卷，那么MIRAGE则是由17个能力强大的大模型联合命题，形成一套高难度、 又有代表性的检测试卷。"论文通讯作 ...

近日，OpenAI发布新一代人工智能模型GPT-5，再次引发全球关注。随着DeepSeek、ChatGPT、通义千 问、豆包等AIGC国产大模型逐渐变成人们学习、工作中的"生产力工具"，其伴生问题也日益凸显：AI 经常会"一本正经地胡说八道"，生成看似合理的虚假信息，即"AI幻觉"；依赖AI工具代写作业甚至毕业 论文，冲击着学术诚信和规范；论文AI率检测系统有待完善，论文被误判的问题时有发生……如何精 准识别AI生成内容，成为亟待解决的热点问题。 近日，南开大学计算机学院媒体计算实验室取得最新研究成果，不仅从评估的角度揭示了现有AI检测 方法的性能不足，还创新性地提出了"直接差异学习"优化策略，教会AI用"火眼金睛"辨别人机不同，实 现AI检测性能的突破。相关成果论文已被计算机多媒体领域国际顶级会议ACM MM2025接收。 "我们的检测器如同有了'火眼金睛'，即便只'学习'过DeepSeek-R1的文本，也能精准识别像GPT-5这样最 新大模型生成的内容。"付嘉晨说。 团队还提出了一个全面的测试基准数据集MIRAGE，使用13种主流的商用大模型（如豆包、DeepSeek、 Kimi等）以及4种先进的开源大模 ...

Core Viewpoint - The rapid development of AI technology has led to an increase in the ability of AI to generate academic papers, raising concerns in the academic and educational sectors regarding the detection of AI-generated content in student theses [1]. Group 1: AI Detection Issues - Some universities require students' theses to not only pass plagiarism checks but also to be evaluated for AI-generated content (AIGC), with a threshold of 15% AI detection rate [1][4]. - A case was reported where a student's thesis was flagged with a significantly higher AI detection rate on a subsequent check, despite being the same document, indicating potential inconsistencies in detection systems [1][4]. - The AI detection tools have been criticized for misidentifying original content as AI-generated, leading to unnecessary revisions and additional costs for students [4][5]. Group 2: Academic Concerns - A professor from Renmin University expressed frustration when their original research, developed over three years, was flagged as "highly suspected of being AI-generated" by a detection platform [5][6]. - The general consensus among academics is that while plagiarism detection is reliable, AI detection tools are problematic and should not be used as strict criteria for assessing academic integrity [6][8]. - There is a growing concern that the standards for determining whether a paper is AI-generated are still vague, making it difficult to accurately assess the originality of academic work [8][9]. Group 3: Recommendations for Universities - Experts suggest that universities should avoid making AI detection a mandatory graduation requirement and instead focus on guiding students in the appropriate use of AI tools in their research [8][9]. - The transition towards integrating AI in academic research is seen as inevitable, with future evaluations of academic ability likely shifting towards how effectively individuals can collaborate with AI [9].

Core Viewpoint - The increasing reliance on AI detection tools for academic papers raises concerns about their accuracy and potential for misjudgment, leading to debates on the appropriateness of using AI-generated content as a criterion for academic integrity [1][2][3][5][7]. Group 1: AI Detection Tools and Their Impact - A significant number of academic papers are being flagged as "highly suspected AI-generated," even when they are original works, leading to confusion and frustration among students and faculty [1][2]. - Universities are implementing regulations requiring students to disclose the use of AI tools in their thesis work, with some setting thresholds for acceptable AI generation rates [2][6]. - The effectiveness of current AI detection tools is questioned, as they often misidentify human-written content as AI-generated due to similarities in text features [3][5][7]. Group 2: Academic Integrity and AI Usage - There is a growing concern that using AI detection tools as a strict measure of academic integrity may undermine the educational process and lead to misjudgments [3][5][7]. - Faculty members emphasize the importance of teaching students to use AI as a supportive tool rather than a replacement for original thought, advocating for a focus on the process of writing rather than just the final product [9]. - Some institutions are exploring ways to integrate AI into the academic process while maintaining standards of originality and critical thinking [8][9]. Group 3: Student Experiences and Reactions - Students have reported instances of their original work being flagged as AI-generated, prompting them to alter their writing styles to avoid detection [2][3]. - There is a shared sentiment among students that while AI can provide inspiration, the core content must remain their own to uphold academic integrity [3][9]. - The debate continues on how to balance the use of AI in academic settings while ensuring that students develop their own analytical and creative skills [8][9].