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相关论文: The Science of Detecting LLM-Generated Texts

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Large Language Models (LLMs) have revolutionized content creation across digital platforms, offering unprecedented capabilities in natural language generation and understanding. These models enable beneficial applications such as content…

计算与语言 · 计算机科学 2025-08-14 Chi Zhang , Changjia Zhu , Junjie Xiong , Xiaoran Xu , Lingyao Li , Yao Liu , Zhuo Lu

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…

计算与语言 · 计算机科学 2025-01-20 Vinu Sankar Sadasivan , Aounon Kumar , Sriram Balasubramanian , Wenxiao Wang , Soheil Feizi

Developing algorithms to differentiate between machine-generated texts and human-written texts has garnered substantial attention in recent years. Existing methods in this direction typically concern an offline setting where a dataset…

机器学习 · 计算机科学 2025-06-09 Can Chen , Jun-Kun Wang

Writing is a foundational literacy skill that underpins effective communication, fosters critical thinking, facilitates learning across disciplines, and enables individuals to organize and articulate complex ideas. Consequently, writing…

计算与语言 · 计算机科学 2026-03-05 Jiangang Hao

The rapid improvement of language models has raised the specter of abuse of text generation systems. This progress motivates the development of simple methods for detecting generated text that can be used by and explained to non-experts. We…

计算与语言 · 计算机科学 2019-06-11 Sebastian Gehrmann , Hendrik Strobelt , Alexander M. Rush

Large Language Models (LLMs) have garnered considerable interest due to their impressive natural language capabilities, which in conjunction with various emergent properties make them versatile tools in workflows ranging from complex code…

材料科学 · 物理学 2024-10-22 Ge Lei , Ronan Docherty , Samuel J. Cooper

The number of Language Models (LMs) dedicated to processing scientific text is on the rise. Keeping pace with the rapid growth of scientific LMs (SciLMs) has become a daunting task for researchers. To date, no comprehensive surveys on…

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 (LLM) are already widely used to generate content for a variety of online platforms. As we are not able to safely distinguish LLM-generated content from human-produced content, LLM-generated content is used to train…

机器学习 · 计算机科学 2024-06-18 Martin Briesch , Dominik Sobania , Franz Rothlauf

As LLMs increase in accessibility, LLM-generated texts have proliferated across several fields, such as scientific, academic, and creative writing. However, LLMs are not created equally; they may have different architectures and training…

计算与语言 · 计算机科学 2024-12-11 Shantanu Thorat , Tianbao Yang

The recent surge in high-quality open-source Generative AI text models (colloquially: LLMs), as well as efficient finetuning techniques, have opened the possibility of creating high-quality personalized models that generate text attuned to…

计算与语言 · 计算机科学 2025-06-03 Eugenia Iofinova , Andrej Jovanovic , Dan Alistarh

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) have recently gained significant attention due to their remarkable capabilities in performing diverse tasks across various domains. However, a thorough evaluation of these models is crucial before deploying them…

Large Language Models (LLMs) have revolutionised the field of Natural Language Processing (NLP) and have achieved state-of-the-art performance in practically every task in this field. However, the prevalent approach used in text generation,…

计算与语言 · 计算机科学 2024-08-12 Nicolo Micheletti , Samuel Belkadi , Lifeng Han , Goran Nenadic

Large Language Models (LLMs) have achieved unprecedented performance in Natural Language Generation (NLG) tasks. However, many existing studies have shown that they could be misused to generate undesired content. In response, before…

机器学习 · 计算机科学 2023-10-04 Hangfan Zhang , Zhimeng Guo , Huaisheng Zhu , Bochuan Cao , Lu Lin , Jinyuan Jia , Jinghui Chen , Dinghao Wu

Recent years have witnessed remarkable progress made in large language models (LLMs). Such advancements, while garnering significant attention, have concurrently elicited various concerns. The potential of these models is undeniably vast;…

计算与语言 · 计算机科学 2023-09-27 Tianhao Shen , Renren Jin , Yufei Huang , Chuang Liu , Weilong Dong , Zishan Guo , Xinwei Wu , Yan Liu , Deyi Xiong

Large language models (LLMs) have shown significant potential to change how we write, communicate, and create, leading to rapid adoption across society. This dissertation examines how individuals and institutions are adapting to and…

计算与语言 · 计算机科学 2025-06-24 Weixin Liang

Large language models (LLMs) are becoming useful in many domains due to their impressive abilities that arise from large training datasets and large model sizes. However, research on LLM-based approaches to document inconsistency detection…

计算与语言 · 计算机科学 2026-04-09 Nelvin Tan , Yaowen Zhang , James Asikin Cheung , Fusheng Liu , Yu-Ching Shih , Dong Yang

The rapid development of Large Language Models (LLMs) demonstrates remarkable multilingual capabilities in natural language processing, attracting global attention in both academia and industry. To mitigate potential discrimination and…

Large language models (LLMs) have transformed natural language processing, achieving remarkable performance across diverse tasks. However, their impressive fluency often comes at the cost of producing false or fabricated information, a…

计算与语言 · 计算机科学 2026-03-20 Aisha Alansari , Hamzah Luqman