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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…

密码学与安全 · 计算机科学 2024-01-17 Xinlei He , Xinyue Shen , Zeyuan Chen , Michael Backes , Yang Zhang

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.…

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…

计算与语言 · 计算机科学 2023-08-07 Haolan Zhan , Xuanli He , Qiongkai Xu , Yuxiang Wu , Pontus Stenetorp

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…

计算与语言 · 计算机科学 2026-05-25 Chenwang Wu , Yiu-ming Cheung , Bo Han , Defu Lian

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…

计算与语言 · 计算机科学 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

The emergence of large language models (LLMs), such as Generative Pre-trained Transformer 4 (GPT-4) used by ChatGPT, has profoundly impacted the academic and broader community. While these models offer numerous advantages in terms of…

计算与语言 · 计算机科学 2024-01-17 Zhicheng Dou , Yuchen Guo , Ching-Chun Chang , Huy H. Nguyen , Isao Echizen

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…

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…

计算与语言 · 计算机科学 2025-02-18 Ran Li , Wei Hao , Weiliang Zhao , Junfeng Yang , Chengzhi Mao

Recent advancements in Large Language Models (LLMs) and their increased accessibility have made it easier than ever for students to automatically generate texts, posing new challenges for educational institutions. To enforce norms of…

计算与语言 · 计算机科学 2025-08-12 Lukas Gehring , Benjamin Paaßen

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…

机器学习 · 计算机科学 2024-11-08 Hyunseok Lee , Jihoon Tack , Jinwoo Shin

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…

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…

信息检索 · 计算机科学 2025-09-03 Teddy Lazebnik , Ariel Rosenfeld

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…

计算与语言 · 计算机科学 2024-04-04 Mazal Bethany , Brandon Wherry , Emet Bethany , Nishant Vishwamitra , Anthony Rios , Peyman Najafirad

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…

计算与语言 · 计算机科学 2024-03-01 Shuhai Zhang , Yiliao Song , Jiahao Yang , Yuanqing Li , Bo Han , Mingkui Tan

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,…

We study the problem of determining whether a piece of text has been authored by a human or by a large language model (LLM). Existing state of the art logits-based detectors make use of statistics derived from the log-probability of the…

计算与语言 · 计算机科学 2026-02-03 Hongyi Zhou , Jin Zhu , Pingfan Su , Kai Ye , Ying Yang , Shakeel A O B Gavioli-Akilagun , Chengchun Shi

Large Language Models (LLMs), such as ChatGPT, are reshaping content creation and academic writing. This study investigates the impact of AI-assisted generative revisions on research manuscripts, focusing on heterogeneous adoption patterns…

计算与语言 · 计算机科学 2025-04-21 Cong William Lin , Wu Zhu

The increasing prevalence of large language models (LLMs) has significantly advanced text generation, but the human-like quality of LLM outputs presents major challenges in reliably distinguishing between human-authored and LLM-generated…

计算与语言 · 计算机科学 2024-12-18 Zhen Tao , Yanfang Chen , Dinghao Xi , Zhiyu Li , Wei Xu

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…

计算与语言 · 计算机科学 2024-11-12 Yongye Su , Yuqing Wu

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…

计算与语言 · 计算机科学 2024-10-21 Zhen Tao , Zhiyu Li , Runyu Chen , Dinghao Xi , Wei Xu
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