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In this paper, a tool for detecting LLM AI text generation is developed based on the Transformer model, aiming to improve the accuracy of AI text generation detection and provide reference for subsequent research. Firstly the text is…

Computation and Language · Computer Science 2024-05-14 Yuhong Mo , Hao Qin , Yushan Dong , Ziyi Zhu , Zhenglin Li

The powerful ability to understand, follow, and generate complex language emerging from large language models (LLMs) makes LLM-generated text flood many areas of our daily lives at an incredible speed and is widely accepted by humans. As…

Computation and Language · Computer Science 2024-04-22 Junchao Wu , Shu Yang , Runzhe Zhan , Yulin Yuan , Derek F. Wong , Lidia S. Chao

With the recent proliferation of Large Language Models (LLMs), there has been an increasing demand for tools to detect machine-generated text. The effective detection of machine-generated text face two pertinent problems: First, they are…

Computation and Language · Computer Science 2024-04-04 Mazal Bethany , Brandon Wherry , Emet Bethany , Nishant Vishwamitra , Anthony Rios , Peyman Najafirad

The ease of access to large language models (LLMs) has enabled a widespread of machine-generated texts, and now it is often hard to tell whether a piece of text was human-written or machine-generated. This raises concerns about potential…

Recent advances in natural language processing (NLP) may enable artificial intelligence (AI) models to generate writing that is identical to human written form in the future. This might have profound ethical, legal, and social…

Machine Learning · Computer Science 2024-04-17 Nuzhat Prova

Large language models (LLMs) present significant risks when used to generate non-factual content and spread disinformation at scale. Detecting such LLM-generated content is crucial, yet current detectors often struggle to generalize in…

Computation and Language · Computer Science 2025-02-18 Ran Li , Wei Hao , Weiliang Zhao , Junfeng Yang , Chengzhi Mao

The rapid advancement of Large Language Models (LLMs) has ushered in an era where AI-generated text is increasingly indistinguishable from human-generated content. Detecting AI-generated text has become imperative to combat misinformation,…

Computation and Language · Computer Science 2024-06-12 Ye Zhang , Qian Leng , Mengran Zhu , Rui Ding , Yue Wu , Jintong Song , Yulu Gong

While recent advancements in the capabilities and widespread accessibility of generative language models, such as ChatGPT (OpenAI, 2022), have brought about various benefits by generating fluent human-like text, the task of distinguishing…

Computation and Language · Computer Science 2023-09-15 Mahdi Dhaini , Wessel Poelman , Ege Erdogan

Our research focuses on the crucial challenge of discerning text produced by Large Language Models (LLMs) from human-generated text, which holds significance for various applications. With ongoing discussions about attaining a model with…

Computation and Language · Computer Science 2023-11-28 Raghav Gaggar , Ashish Bhagchandani , Harsh Oza

Large language models (LLMs) have demonstrated remarkable capability to generate fluent responses to a wide variety of user queries. However, this has also raised concerns about the potential misuse of such texts in journalism, education,…

The development of Generative AI Large Language Models (LLMs) raised the alarm regarding identifying content produced through generative AI or humans. In one case, issues arise when students heavily rely on such tools in a manner that can…

Computation and Language · Computer Science 2025-01-07 Ayat Najjar , Huthaifa I. Ashqar , Omar Darwish , Eman Hammad

With the widespread use of large language models (LLMs), many researchers have turned their attention to detecting text generated by them. However, there is no consistent or precise definition of their target, namely "LLM-generated text".…

Computation and Language · Computer Science 2025-10-24 Mingmeng Geng , Thierry Poibeau

Detecting AI-generated text is a difficult problem to begin with; detecting AI-generated text on social media is made even more difficult due to the short text length and informal, idiosyncratic language of the internet. It is nonetheless…

Computation and Language · Computer Science 2025-06-17 Hillary Dawkins , Kathleen C. Fraser , Svetlana Kiritchenko

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

Large Language Models (LLMs) perform impressively well in various applications. However, the potential for misuse of these models in activities such as plagiarism, generating fake news, and spamming has raised concern about their…

Computation and Language · Computer Science 2025-01-20 Vinu Sankar Sadasivan , Aounon Kumar , Sriram Balasubramanian , Wenxiao Wang , Soheil Feizi

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

Large Language Models (LLMs), such as GPT-3 and BERT, reshape how textual content is written and communicated. These models have the potential to generate scientific content that is indistinguishable from that written by humans. Hence, LLMs…

Computation and Language · Computer Science 2024-11-19 Bushra Alhijawi , Rawan Jarrar , Aseel AbuAlRub , Arwa Bader

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

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