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We find that large language models (LLMs) are more likely to modify human-written text than AI-generated text when tasked with rewriting. This tendency arises because LLMs often perceive AI-generated text as high-quality, leading to fewer…

Computation and Language · Computer Science 2024-04-16 Chengzhi Mao , Carl Vondrick , Hao Wang , Junfeng Yang

The growing use of large language models (LLMs) for text generation has led to widespread concerns about AI-generated content detection. However, an overlooked challenge is AI-polished text, where human-written content undergoes subtle…

Computation and Language · Computer Science 2025-05-06 Shoumik Saha , Soheil Feizi

ChatGPT has become a global sensation. As ChatGPT and other Large Language Models (LLMs) emerge, concerns of misusing them in various ways increase, such as disseminating fake news, plagiarism, manipulating public opinion, cheating, and…

Machine Learning · Computer Science 2023-04-06 Alessandro Pegoraro , Kavita Kumari , Hossein Fereidooni , Ahmad-Reza Sadeghi

This paper introduces AIDetx, a novel method for detecting machine-generated text using data compression techniques. Traditional approaches, such as deep learning classifiers, often suffer from high computational costs and limited…

Computation and Language · Computer Science 2024-12-02 Leonardo Almeida , Pedro Rodrigues , Diogo Magalhães , Armando J. Pinho , Diogo Pratas

With the rapid development and widespread application of Large Language Models (LLMs), the use of Machine-Generated Text (MGT) has become increasingly common, bringing with it potential risks, especially in terms of quality and integrity in…

Computation and Language · Computer Science 2024-04-02 Qihui Zhang , Chujie Gao , Dongping Chen , Yue Huang , Yixin Huang , Zhenyang Sun , Shilin Zhang , Weiye Li , Zhengyan Fu , Yao Wan , Lichao Sun

Generation of Artificial Intelligence (AI) texts in important works has become a common practice that can be used to misuse and abuse AI at various levels. Traditional AI detectors often rely on document-level classification, which…

Computation and Language · Computer Science 2025-09-24 Lekkala Sai Teja , Annepaka Yadagiri , Partha Pakray , Chukhu Chunka , Mangadoddi Srikar Vardhan

Large language models (LLMs) have achieved human-level text generation, emphasizing the need for effective AI-generated text detection to mitigate risks like the spread of fake news and plagiarism. Existing research has been constrained by…

Computation and Language · Computer Science 2024-05-22 Yafu Li , Qintong Li , Leyang Cui , Wei Bi , Zhilin Wang , Longyue Wang , Linyi Yang , Shuming Shi , Yue Zhang

The growing capability of large language models to produce fluent, contextually coherent text has created mounting pressure on the systems and institutions responsible for ensuring the authenticity of digital content. Advanced generative…

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 rise of LLMs (Large Language Models) has contributed to the improved performance and development of cutting-edge NLP applications. However, these can also pose risks when used maliciously, such as spreading fake news, harmful content,…

Computation and Language · Computer Science 2025-02-18 Lucía Yan Wu , Isabel Segura-Bedmar

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) are now capable of generating text that closely resembles human writing, making them powerful tools for content creation, but this growing ability has also made it harder to tell whether a piece of text was…

Computation and Language · Computer Science 2025-10-21 Muhammad Ammar , Hadiya Murad Hadi , Usman Majeed Butt

Recent advances in generative pre-trained transformer large language models have emphasised the potential risks of unfair use of artificial intelligence (AI) generated content in an academic environment and intensified efforts in searching…

The rapid adoption of large language models (LLMs) such as ChatGPT has blurred the line between human and AI-generated texts, raising urgent questions about academic integrity, intellectual property, and the spread of misinformation. Thus,…

Computation and Language · Computer Science 2025-09-26 Sharanya Parimanoharan , Ruwan D. Nawarathna

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

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

As large language models (LLMs) become increasingly prevalent, reliable methods for detecting AI-generated text are critical for mitigating potential risks. We introduce DependencyAI, a simple and interpretable approach for detecting…

Computation and Language · Computer Science 2026-02-18 Sara Ahmed , Tracy Hammond

The proliferation of AI-generated media poses significant challenges to information authenticity and social trust, making reliable detection methods highly demanded. Methods for detecting AI-generated media have evolved rapidly, paralleling…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Yueying Zou , Peipei Li , Zekun Li , Huaibo Huang , Xing Cui , Xuannan Liu , Chenghanyu Zhang , Ran He

The emergence of large language models (LLMs) has resulted in the production of LLM-generated texts that is highly sophisticated and almost indistinguishable from texts written by humans. However, this has also sparked concerns about the…

Computation and Language · Computer Science 2023-06-06 Ruixiang Tang , Yu-Neng Chuang , Xia Hu

Recent Large Language Models (LLMs) have demonstrated remarkable capabilities in generating text that closely resembles human writing across wide range of styles and genres. However, such capabilities are prone to potential abuse, such as…

Computation and Language · Computer Science 2023-11-09 Harika Abburi , Kalyani Roy , Michael Suesserman , Nirmala Pudota , Balaji Veeramani , Edward Bowen , Sanmitra Bhattacharya