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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 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

With the rapid progress of large language models (LLMs) and the huge amount of text they generated, it becomes more and more impractical to manually distinguish whether a text is machine-generated. Given the growing use of LLMs in social…

Computation and Language · Computer Science 2023-06-12 Jinyan Su , Terry Yue Zhuo , Di Wang , Preslav Nakov

With the widespread use of large language models (LLMs), many researchers have turned their attention to detecting text generated by them. However, there is no consistent or precise definition of their target, namely "LLM-generated text".…

Computation and Language · Computer Science 2025-10-24 Mingmeng Geng , Thierry Poibeau

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…

Information Retrieval · Computer Science 2025-09-03 Teddy Lazebnik , Ariel Rosenfeld

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

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

This article gives an overview of the field of LLM text recognition. Different approaches and implemented detectors for the recognition of LLM-generated text are presented. In addition to discussing the implementations, the article focuses…

Computation and Language · Computer Science 2024-06-18 Thorsten Pröhl , Erik Putzier , Rüdiger Zarnekow

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

With the emergence of widely available powerful LLMs, disinformation generated by large Language Models (LLMs) has become a major concern. Historically, LLM detectors have been touted as a solution, but their effectiveness in the real world…

Computation and Language · Computer Science 2024-09-30 Henrique Da Silva Gameiro , Andrei Kucharavy , Ljiljana Dolamic

Detecting text generated by modern large language models is thought to be hard, as both LLMs and humans can exhibit a wide range of complex behaviors. However, we find that a score based on contrasting two closely related language models is…

Computation and Language · Computer Science 2024-10-15 Abhimanyu Hans , Avi Schwarzschild , Valeriia Cherepanova , Hamid Kazemi , Aniruddha Saha , Micah Goldblum , Jonas Geiping , Tom Goldstein

The emergence of large language models (LLMs) has resulted in the production of LLM-generated texts that is highly sophisticated and almost indistinguishable from texts written by humans. However, this has also sparked concerns about the…

Computation and Language · Computer Science 2023-06-06 Ruixiang Tang , Yu-Neng Chuang , Xia Hu

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 increasing fluency and widespread usage of large language models (LLMs) highlight the desirability of corresponding tools aiding detection of LLM-generated text. In this paper, we identify a property of the structure of an LLM's…

Computation and Language · Computer Science 2023-07-25 Eric Mitchell , Yoonho Lee , Alexander Khazatsky , Christopher D. Manning , Chelsea Finn

The rampant proliferation of large language models, fluent enough to generate text indistinguishable from human-written language, gives unprecedented importance to the detection of machine-generated text. This work is motivated by an…

Computation and Language · Computer Science 2023-10-10 Xiao Pu , Jingyu Zhang , Xiaochuang Han , Yulia Tsvetkov , Tianxing He

To combat the potential misuse of Natural Language Generation (NLG) technology, a variety of algorithms have been developed for the detection of AI-generated texts. Traditionally, this task is treated as a binary classification problem.…

Computation and Language · Computer Science 2023-12-22 Yi-Fan Zhang , Zhang Zhang , Liang Wang , Tieniu Tan , Rong Jin

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 capabilities in generating high-quality texts across diverse domains. However, the potential misuse of LLMs has raised significant concerns, underscoring the urgent need for reliable…

Computation and Language · Computer Science 2024-10-10 Yihuai Xu , Yongwei Wang , Yifei Bi , Huangsen Cao , Zhouhan Lin , Yu Zhao , Fei Wu

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…

Computation and Language · Computer Science 2024-12-18 Zhen Tao , Yanfang Chen , Dinghao Xi , Zhiyu Li , Wei Xu

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
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