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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

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

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

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

Large Language Models (LLMs) have revolutionized text generation, making detecting machine-generated text increasingly challenging. Although past methods have achieved good performance on detecting pure machine-generated text, those…

Computation and Language · Computer Science 2024-12-24 Jiaqi Chen , Xiaoye Zhu , Tianyang Liu , Ying Chen , Xinhui Chen , Yiwen Yuan , Chak Tou Leong , Zuchao Li , Tang Long , Lei Zhang , Chenyu Yan , Guanghao Mei , Jie Zhang , Lefei Zhang

Personality detection aims to detect one's personality traits underlying in social media posts. One challenge of this task is the scarcity of ground-truth personality traits which are collected from self-report questionnaires. Most existing…

Computation and Language · Computer Science 2024-03-13 Linmei Hu , Hongyu He , Duokang Wang , Ziwang Zhao , Yingxia Shao , Liqiang Nie

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

The widespread adoption of Large Language Models (LLMs) has made the detection of AI-Generated text a pressing and complex challenge. Although many detection systems report high benchmark accuracy, their reliability in real-world settings…

Computation and Language · Computer Science 2026-04-23 Shushanta Pudasaini , Luis Miralles-Pechuán , David Lillis , Marisa Llorens Salvador

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

The rapid adoption of large language models (LLMs), such as GPT-4 and Claude 3.5, underscores the need to distinguish LLM-generated text from human-written content to mitigate the spread of misinformation and misuse in education. One…

Machine Learning · Statistics 2025-11-11 Xingchi Li , Xiaochi Liu , Guanxun Li

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

Despite considerable progress in the development of machine-text detectors, it has been suggested that the problem is inherently hard, and therefore, that stakeholders should proceed under the assumption that machine-generated text cannot…

Computation and Language · Computer Science 2025-09-30 Rafael Rivera Soto , Barry Chen , Nicholas Andrews

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

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

As Large Language Models (LLMs) become increasingly prevalent, their generated outputs are proliferating across the web, risking a future where machine-generated content dilutes human-authored text. Since online data is the primary resource…

Computation and Language · Computer Science 2025-09-23 George Drayson , Emine Yilmaz , Vasileios Lampos

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

Large language models (LLMs) have reached human-like proficiency in generating diverse textual content, underscoring the necessity for effective fake text detection to avoid potential risks such as fake news in social media. Previous…

Machine Learning · Computer Science 2024-03-21 Zhixin Lai , Xuesheng Zhang , Suiyao Chen

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

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
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