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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

Large language models (LLMs) have opened up enormous opportunities while simultaneously posing ethical dilemmas. One of the major concerns is their ability to create text that closely mimics human writing, which can lead to potential…

计算与语言 · 计算机科学 2023-11-15 Zhen Guo , Shangdi Yu

Large language models (LLMs) have shown remarkable performance in various tasks and have been extensively utilized by the public. However, the increasing concerns regarding the misuse of LLMs, such as plagiarism and spamming, have led to…

计算与语言 · 计算机科学 2024-05-16 Ning Lu , Shengcai Liu , Rui He , Qi Wang , Yew-Soon Ong , Ke Tang

As Large Language Models (LLMs) become increasingly sophisticated, they raise significant security concerns, including the creation of fake news and academic misuse. Most detectors for identifying model-generated text are limited by their…

密码学与安全 · 计算机科学 2024-10-10 Zhenyu Xu , Victor S. Sheng

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

The increasing use of Artificial Intelligence (AI) technologies, such as Large Language Models (LLMs) has led to nontrivial improvements in various tasks, including accurate authorship identification of documents. However, while LLMs…

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

Large Language Models (LLMs) can generate highly persuasive text, raising concerns about their misuse for propaganda, manipulation, and other harmful purposes. This leads us to our central question: Is LLM-generated persuasion more…

计算与语言 · 计算机科学 2026-04-22 Arkadiusz Modzelewski , Paweł Golik , Anna Kołos , Giovanni Da San Martino

The widespread adoption of ChatGPT has raised concerns about its misuse, highlighting the need for robust detection of AI-generated text. Current word-level detectors are vulnerable to paraphrasing or simple prompts (PSP), suffer from…

计算与语言 · 计算机科学 2025-09-24 Mo Mu , Dianqiao Lei , Chang Li

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

The rapid advancement of large language models (LLMs) has blurred the line between AI-generated and human-written text. This progress brings societal risks such as misinformation, authorship ambiguity, and intellectual property concerns,…

计算与语言 · 计算机科学 2025-10-10 Xiaowei Zhu , Yubing Ren , Fang Fang , Qingfeng Tan , Shi Wang , Yanan Cao

Large Language Model (LLM) watermarking embeds detectable signals into generated text for copyright protection, misuse prevention, and content detection. While prior studies evaluate robustness using watermark removal attacks, these methods…

密码学与安全 · 计算机科学 2025-09-16 Zhaoxi Zhang , Xiaomei Zhang , Yanjun Zhang , He Zhang , Shirui Pan , Bo Liu , Asif Qumer Gill , Leo Yu Zhang

Prior studies have shown that distinguishing text generated by Large Language Models (LLMs) from human-written one is highly challenging for humans, and often no better than random guessing. To verify the generalizability of this finding…

The widespread use of large language models (LLMs) has sparked concerns about the potential misuse of AI-generated text, as these models can produce content that closely resembles human-generated text. Current detectors for AI-generated…

计算与语言 · 计算机科学 2024-06-27 Guanhua Huang , Yuchen Zhang , Zhe Li , Yongjian You , Mingze Wang , Zhouwang Yang

We have witnessed lately a rapid proliferation of advanced Large Language Models (LLMs) capable of generating high-quality text. While these LLMs have revolutionized text generation across various domains, they also pose significant risks…

计算与语言 · 计算机科学 2024-03-05 Tharindu Kumarage , Garima Agrawal , Paras Sheth , Raha Moraffah , Aman Chadha , Joshua Garland , Huan Liu

The growing capability of large language models to produce fluent, contextually coherent text has created mounting pressure on the systems and institutions responsible for ensuring the authenticity of digital content. Advanced generative…

As large language models (LLMs) become increasingly prevalent, reliable methods for detecting AI-generated text are critical for mitigating potential risks. We introduce DependencyAI, a simple and interpretable approach for detecting…

计算与语言 · 计算机科学 2026-02-18 Sara Ahmed , Tracy Hammond

Machine generated text is increasingly difficult to distinguish from human authored text. Powerful open-source models are freely available, and user-friendly tools that democratize access to generative models are proliferating. ChatGPT,…

计算与语言 · 计算机科学 2023-05-09 Evan Crothers , Nathalie Japkowicz , Herna Viktor

The rise of LLMs (Large Language Models) has contributed to the improved performance and development of cutting-edge NLP applications. However, these can also pose risks when used maliciously, such as spreading fake news, harmful content,…

计算与语言 · 计算机科学 2025-02-18 Lucía Yan Wu , Isabel Segura-Bedmar

Detecting content generated by large language models (LLMs) is crucial for preventing misuse and building trustworthy AI systems. Although existing detection methods perform well, their robustness in out-of-distribution (OOD) scenarios is…

计算与语言 · 计算机科学 2025-08-19 Xin Chen , Junchao Wu , Shu Yang , Runzhe Zhan , Zeyu Wu , Ziyang Luo , Di Wang , Min Yang , Lidia S. Chao , Derek F. Wong