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Since the proliferation of LLMs, there have been concerns about their misuse for harmful content creation and spreading. Recent studies justify such fears, providing evidence of LLM vulnerabilities and high potential of their misuse. Humans…

Computation and Language · Computer Science 2025-03-20 Dominik Macko , Robert Moro , Ivan Srba

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

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 spread of fake news has emerged as a critical challenge, undermining trust and posing threats to society. In the era of Large Language Models (LLMs), the capability to generate believable fake content has intensified these concerns. In…

Computation and Language · Computer Science 2023-09-19 Jinyan Su , Terry Yue Zhuo , Jonibek Mansurov , Di Wang , Preslav Nakov

Large Language Models (LLMs) have revolutionized the domain of natural language processing (NLP) with remarkable capabilities of generating human-like text responses. However, despite these advancements, several works in the existing…

Computation and Language · Computer Science 2023-10-25 Soumya Suvra Ghosal , Souradip Chakraborty , Jonas Geiping , Furong Huang , Dinesh Manocha , Amrit Singh Bedi

The increasing capability of large language models (LLMs) to generate fluent long-form texts is presenting new challenges in distinguishing machine-generated outputs from human-written ones, which is crucial for ensuring authenticity and…

Computation and Language · Computer Science 2024-10-08 Yufei Tian , Zeyu Pan , Nanyun Peng

Nowadays, powerful large language models (LLMs) such as ChatGPT have demonstrated revolutionary power in a variety of tasks. Consequently, the detection of machine-generated texts (MGTs) is becoming increasingly crucial as LLMs become more…

Cryptography and Security · Computer Science 2024-01-17 Xinlei He , Xinyue Shen , Zeyuan Chen , Michael Backes , Yang Zhang

Large Language Models (LLMs) are gearing up to surpass human creativity. The veracity of the statement needs careful consideration. In recent developments, critical questions arise regarding the authenticity of human work and the…

Computation and Language · Computer Science 2025-09-29 Sai Teja Lekkala , Yadagiri Annepaka , Arun Kumar Challa , Samatha Reddy Machireddy , Partha Pakray , Chukhu Chunka

Large language models (LLMs) have transformed human writing by enhancing grammar correction, content expansion, and stylistic refinement. However, their widespread use raises concerns about authorship, originality, and ethics, even…

Computation and Language · Computer Science 2024-10-21 Zhen Tao , Zhiyu Li , Runyu Chen , Dinghao Xi , Wei Xu

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

Text generative models (TGMs) excel in producing text that matches the style of human language reasonably well. Such TGMs can be misused by adversaries, e.g., by automatically generating fake news and fake product reviews that can look…

Computation and Language · Computer Science 2020-11-04 Ganesh Jawahar , Muhammad Abdul-Mageed , Laks V. S. Lakshmanan

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

The ability of large language models to generate complex texts allows them to be widely integrated into many aspects of life, and their output can quickly fill all network resources. As the impact of LLMs grows, it becomes increasingly…

Computation and Language · Computer Science 2024-11-12 Yongye Su , Yuqing Wu

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

The remarkable capabilities and easy accessibility of large language models (LLMs) have significantly increased societal risks (e.g., fake news generation), necessitating the development of LLM-generated text (LGT) detection methods for…

Machine Learning · Computer Science 2024-11-08 Hyunseok Lee , Jihoon Tack , Jinwoo Shin

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

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

Large language models (LLMs) such as ChatGPT have exhibited remarkable performance in generating human-like texts. However, machine-generated texts (MGTs) may carry critical risks, such as plagiarism issues, misleading information, or…

Computation and Language · Computer Science 2024-03-01 Shuhai Zhang , Yiliao Song , Jiahao Yang , Yuanqing Li , Bo Han , Mingkui Tan

Large Language Models (LLMs) possess an extraordinary capability to produce text that is not only coherent and contextually relevant but also strikingly similar to human writing. They adapt to various styles and genres, producing content…

Computation and Language · Computer Science 2025-07-08 Chinnappa Guggilla , Budhaditya Roy , Trupti Ramdas Chavan , Abdul Rahman , Edward Bowen

Machine-Generated Text (MGT) detection aims to identify a piece of text as machine or human written. Prior work has primarily formulated MGT detection as a binary classification task over an entire document, with limited work exploring…

Computation and Language · Computer Science 2024-06-12 Zhongping Zhang , Wenda Qin , Bryan A. Plummer
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