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Detecting texts generated by Large Language Models (LLMs) could cause grave mistakes due to incorrect decisions, such as undermining students' academic dignity. LLM text detection thus needs to ensure the interpretability of the decision,…

Computation and Language · Computer Science 2026-05-06 Ryuto Koike , Masahiro Kaneko , Ayana Niwa , Preslav Nakov , Naoaki Okazaki

Large language models (LLMs) such as GPT, Claude, Gemini, and Grok have been deeply integrated into our daily life. They now support a wide range of tasks -- from dialogue and email drafting to assisting with teaching and coding, serving as…

Computation and Language · Computer Science 2026-01-13 Hongyi Zhou , Jin Zhu , Ying Yang , Chengchun Shi

General large language models (LLMs) such as ChatGPT have shown remarkable success, but it has also raised concerns among people about the misuse of AI-generated texts. Therefore, an important question is how to detect whether the texts are…

Computation and Language · Computer Science 2023-10-24 Rongsheng Wang , Qi Li , Sihong Xie

The increasing fluency and widespread usage of large language models (LLMs) highlight the desirability of corresponding tools aiding detection of LLM-generated text. In this paper, we identify a property of the structure of an LLM's…

Computation and Language · Computer Science 2023-07-25 Eric Mitchell , Yoonho Lee , Alexander Khazatsky , Christopher D. Manning , Chelsea Finn

The rising popularity of large language models (LLMs) has raised concerns about machine-generated text (MGT), particularly in academic settings, where issues like plagiarism and misinformation are prevalent. As a result, developing a highly…

Artificial Intelligence · Computer Science 2025-08-05 Yule Liu , Zhiyuan Zhong , Yifan Liao , Zhen Sun , Jingyi Zheng , Jiaheng Wei , Qingyuan Gong , Fenghua Tong , Yang Chen , Yang Zhang , Xinlei He

Large language models (LLMs) have opened up enormous opportunities while simultaneously posing ethical dilemmas. One of the major concerns is their ability to create text that closely mimics human writing, which can lead to potential…

Computation and Language · Computer Science 2023-11-15 Zhen Guo , Shangdi Yu

Widely applied large language models (LLMs) can generate human-like content, raising concerns about the abuse of LLMs. Therefore, it is important to build strong AI-generated text (AIGT) detectors. Current works only consider document-level…

Computation and Language · Computer Science 2023-12-18 Pengyu Wang , Linyang Li , Ke Ren , Botian Jiang , Dong Zhang , Xipeng Qiu

Large Language Models (LLMs), exemplified by ChatGPT, have significantly reshaped text generation, particularly in the realm of writing assistance. While ethical considerations underscore the importance of transparently acknowledging LLM…

Information Retrieval · Computer Science 2025-09-03 Teddy Lazebnik , Ariel Rosenfeld

Large language models (LLMs) such as ChatGPT are increasingly being used for various use cases, including text content generation at scale. Although detection methods for such AI-generated text exist already, we investigate ChatGPT's…

Computation and Language · Computer Science 2023-08-21 Amrita Bhattacharjee , Huan Liu

Generated texts from large language models (LLMs) are remarkably close to high-quality human-authored text, raising concerns about their potential misuse in spreading false information and academic misconduct. Consequently, there is an…

Computation and Language · Computer Science 2023-11-06 Kangxi Wu , Liang Pang , Huawei Shen , Xueqi Cheng , Tat-Seng Chua

Recent advancements in Generative AI and Large Language Models (LLMs) have enabled the creation of highly realistic synthetic content, raising concerns about the potential for malicious use, such as misinformation and manipulation.…

Computation and Language · Computer Science 2025-06-02 Andrea Pedrotti , Michele Papucci , Cristiano Ciaccio , Alessio Miaschi , Giovanni Puccetti , Felice Dell'Orletta , Andrea Esuli

The potential of artificial intelligence (AI)-based large language models (LLMs) holds considerable promise in revolutionizing education, research, and practice. However, distinguishing between human-written and AI-generated text has become…

Computation and Language · Computer Science 2023-11-14 Kadhim Hayawi , Sakib Shahriar , Sujith Samuel Mathew

ChatGPT and other general large language models (LLMs) have achieved remarkable success, but they have also raised concerns about the misuse of AI-generated texts. Existing AI-generated text detection models, such as based on BERT and…

Computation and Language · Computer Science 2024-02-05 Rongsheng Wang , Haoming Chen , Ruizhe Zhou , Han Ma , Yaofei Duan , Yanlan Kang , Songhua Yang , Baoyu Fan , Tao Tan

Detecting text generated by large language models (LLMs) is of great recent interest. With zero-shot methods like DetectGPT, detection capabilities have reached impressive levels. However, the reliability of existing detectors in real-world…

Computation and Language · Computer Science 2025-03-13 Junchao Wu , Runzhe Zhan , Derek F. Wong , Shu Yang , Xinyi Yang , Yulin Yuan , Lidia S. Chao

Large language models (LLMs) have shown the ability to produce fluent and cogent content, presenting both productivity opportunities and societal risks. To build trustworthy AI systems, it is imperative to distinguish between…

Computation and Language · Computer Science 2024-12-17 Guangsheng Bao , Yanbin Zhao , Zhiyang Teng , Linyi Yang , Yue Zhang

The rise of large language models (LLMs) has created an urgent need to distinguish between human-written and LLM-generated text to ensure authenticity and societal trust. Existing detectors typically provide a binary classification for an…

Computation and Language · Computer Science 2026-05-06 Mengchu Li , Jin Zhu , Jinglai Li , Chengchun Shi

In this paper, we study how well humans can detect text generated by commercial LLMs (GPT-4o, Claude, o1). We hire annotators to read 300 non-fiction English articles, label them as either human-written or AI-generated, and provide…

Computation and Language · Computer Science 2025-05-21 Jenna Russell , Marzena Karpinska , Mohit Iyyer

The burgeoning progress in the field of Large Language Models (LLMs) heralds significant benefits due to their unparalleled capacities. However, it is critical to acknowledge the potential misuse of these models, which could give rise to a…

Computation and Language · Computer Science 2023-08-07 Haolan Zhan , Xuanli He , Qiongkai Xu , Yuxiang Wu , Pontus Stenetorp

Detecting content generated by large language models (LLMs) is crucial for preventing misuse and building trustworthy AI systems. Although existing detection methods perform well, their robustness in out-of-distribution (OOD) scenarios is…

Computation and Language · Computer Science 2025-08-19 Xin Chen , Junchao Wu , Shu Yang , Runzhe Zhan , Zeyu Wu , Ziyang Luo , Di Wang , Min Yang , Lidia S. Chao , Derek F. Wong

Educators are increasingly concerned about the usage of Large Language Models (LLMs) such as ChatGPT in programming education, particularly regarding the potential exploitation of imperfections in Artificial Intelligence Generated Content…

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