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Related papers: Detecting Machine-Generated Texts by Multi-Populat…

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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

Machine-generated texts (MGTs) produced by large language models (LLMs) are increasingly prevalent across various applications, while their potential misuse in fake news propagation and phishing has raised serious concerns, highlighting the…

Computation and Language · Computer Science 2026-05-25 Chenwang Wu , Yiu-ming Cheung , Bo Han , Defu Lian

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

The advent of Large Language Models (LLMs) has brought an unprecedented surge in machine-generated text (MGT) across diverse channels. This raises legitimate concerns about its potential misuse and societal implications. The need to…

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

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 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

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) 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

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

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,…

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

We propose a method to optimize the representation and distinguishability of samples from two probability distributions, by maximizing the estimated power of a statistical test based on the maximum mean discrepancy (MMD). This optimized MMD…

Recent releases of Large Language Models (LLMs), e.g. ChatGPT, are astonishing at generating human-like texts, but they may impact the authenticity of texts. Previous works proposed methods to detect these AI-generated texts, including…

Computation and Language · Computer Science 2024-03-06 Yuchuan Tian , Hanting Chen , Xutao Wang , Zheyuan Bai , Qinghua Zhang , Ruifeng Li , Chao Xu , Yunhe Wang

The large language models (LLMs) are able to generate high-quality texts in multiple languages. Such texts are often not recognizable by humans as generated, and therefore present a potential of LLMs for misuse (e.g., plagiarism, spams,…

Computation and Language · Computer Science 2025-09-25 Dominik Macko

Our work addresses the critical issue of distinguishing text generated by Large Language Models (LLMs) from human-produced text, a task essential for numerous applications. Despite ongoing debate about the feasibility of such…

Computation and Language · Computer Science 2023-10-04 Souradip Chakraborty , Amrit Singh Bedi , Sicheng Zhu , Bang An , Dinesh Manocha , Furong Huang

Large language models (LLMs) have gained significant attention due to their ability to mimic human language. Identifying texts generated by LLMs is crucial for understanding their capabilities and mitigating potential consequences. This…

Computation and Language · Computer Science 2024-07-19 Anjali Rawal , Hui Wang , Youjia Zheng , Yu-Hsuan Lin , Shanu Sushmita

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

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
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