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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

To combat the misuse of Large Language Models (LLMs), many recent studies have presented LLM-generated-text detectors with promising performance. When users instruct LLMs to generate texts, the instruction can include different constraints…

Computation and Language · Computer Science 2024-10-02 Ryuto Koike , Masahiro Kaneko , Naoaki Okazaki

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…

Computation and Language · Computer Science 2025-08-12 Lukas Gehring , Benjamin Paaßen

The prevalence and strong capability of large language models (LLMs) present significant safety and ethical risks if exploited by malicious users. To prevent the potentially deceptive usage of LLMs, recent works have proposed algorithms to…

Computation and Language · Computer Science 2023-10-20 Zhouxing Shi , Yihan Wang , Fan Yin , Xiangning Chen , Kai-Wei Chang , Cho-Jui Hsieh

The effective detection and governance of Large Language Model (LLM) generated content has become increasingly critical due to the growing risk of misuse. Despite the impressive performance of existing detectors, their reliability and…

Computation and Language · Computer Science 2026-05-20 Junchao Wu , Yefeng Liu , Chenyu Zhu , Hao Zhang , Zeyu Wu , Tianqi Shi , Yichao Du , Longyue Wang , Weihua Luo , Jinsong Su , Derek F. Wong

The widespread use of large language models (LLMs) is increasing the demand for methods that detect machine-generated text to prevent misuse. The goal of our study is to stress test the detectors' robustness to malicious attacks under…

Computation and Language · Computer Science 2024-02-20 Yichen Wang , Shangbin Feng , Abe Bohan Hou , Xiao Pu , Chao Shen , Xiaoming Liu , Yulia Tsvetkov , Tianxing He

With the development of large language models (LLMs), detecting whether text is generated by a machine becomes increasingly challenging in the face of malicious use cases like the spread of false information, protection of intellectual…

Computation and Language · Computer Science 2024-04-03 Ying Zhou , Ben He , Le Sun

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) 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 increasing availability of large language models (LLMs) has raised concerns about their potential misuse in online learning. While tools for detecting LLM-generated text exist and are widely used by researchers and educators, their…

Human-Computer Interaction · Computer Science 2025-06-23 Shambhavi Bhushan , Danielle R Thomas , Conrad Borchers , Isha Raghuvanshi , Ralph Abboud , Erin Gatz , Shivang Gupta , Kenneth Koedinger

The increasing capabilities of Large Language Models (LLMs) have raised concerns about their misuse in AI-generated plagiarism and social engineering. While various AI-generated text detectors have been proposed to mitigate these risks,…

Computation and Language · Computer Science 2025-10-31 Yize Cheng , Vinu Sankar Sadasivan , Mehrdad Saberi , Shoumik Saha , Soheil Feizi

The advent of large language models (LLMs) has revolutionized the field of text generation, producing outputs that closely mimic human-like writing. Although academic and industrial institutions have developed detectors to prevent the…

Machine Learning · Computer Science 2025-02-25 Tianchun Wang , Yuanzhou Chen , Zichuan Liu , Zhanwen Chen , Haifeng Chen , Xiang Zhang , Wei Cheng

Detecting text generated by large language models (LLMs) is of great recent interest. With zero-shot methods like DetectGPT, detection capabilities have reached impressive levels. However, the reliability of existing detectors in real-world…

Computation and Language · Computer Science 2025-03-13 Junchao Wu , Runzhe Zhan , Derek F. Wong , Shu Yang , Xinyi Yang , Yulin Yuan , Lidia S. Chao

The widespread adoption of large language models (LLMs) has created an urgent need for robust tools to detect LLM-generated text, especially in light of \textit{paraphrasing} techniques that often evade existing detection methods. To…

Computation and Language · Computer Science 2024-11-21 Weiqing He , Bojian Hou , Tianqi Shang , Davoud Ataee Tarzanagh , Qi Long , Li Shen

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

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

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

With the advent of large language models (LLMs), it has become common practice for users to draft text and utilize LLMs to enhance its quality through paraphrasing. However, this process can sometimes result in the loss or distortion of the…

Computation and Language · Computer Science 2026-01-26 Hoang-Quoc Nguyen-Son , Minh-Son Dao , Koji Zettsu

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) have demonstrated exceptional performance on a range of downstream NLP tasks by generating text that closely resembles human writing. However, the ease of achieving this similarity raises concerns from potential…

Computation and Language · Computer Science 2025-03-25 Beining Xu , Arkaitz Zubiaga
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