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The rapid advancement of large language models (LLMs) has led to increasingly human-like AI-generated text, raising concerns about content authenticity, misinformation, and trustworthiness. Addressing the challenge of reliably detecting…

Large Language Model (LLMs) can be used to write or modify documents, presenting a challenge for understanding the intent behind their use. For example, benign uses may involve using LLM on a human-written document to improve its grammar or…

Computation and Language · Computer Science 2025-09-22 Yitong Wang , Zhongping Zhang , Margherita Piana , Zheng Zhou , Peter Gerstoft , Bryan A. Plummer

With the rise of generative language models, machine-generated text detection has become a critical challenge. A wide variety of models is available, but inconsistent datasets, evaluation metrics, and assessment strategies obscure…

Computation and Language · Computer Science 2026-04-23 Kevin Stowe , Kailash Patil

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

This paper presents a novel approach for detecting ChatGPT-generated vs. human-written text using language models. To this end, we first collected and released a pre-processed dataset named OpenGPTText, which consists of rephrased content…

Computation and Language · Computer Science 2023-05-19 Yutian Chen , Hao Kang , Vivian Zhai , Liangze Li , Rita Singh , Bhiksha Raj

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

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 revolutionized the domain of natural language processing (NLP) with remarkable capabilities of generating human-like text responses. However, despite these advancements, several works in the existing…

Computation and Language · Computer Science 2023-10-25 Soumya Suvra Ghosal , Souradip Chakraborty , Jonas Geiping , Furong Huang , Dinesh Manocha , Amrit Singh Bedi

An ideal detection system for machine generated content is supposed to work well on any generator as many more advanced LLMs come into existence day by day. Existing systems often struggle with accurately identifying AI-generated content…

Nowadays, the usage of Large Language Models (LLMs) has increased, and LLMs have been used to generate texts in different languages and for different tasks. Additionally, due to the participation of remarkable companies such as Google and…

Computation and Language · Computer Science 2024-02-26 Mohammad Heydari Rad , Farhan Farsi , Shayan Bali , Romina Etezadi , Mehrnoush Shamsfard

Detecting Machine-Generated Text (MGT) has emerged as a significant area of study within Natural Language Processing. While language models generate text, they often leave discernible traces, which can be scrutinized using either…

The development of Generative AI Large Language Models (LLMs) raised the alarm regarding identifying content produced through generative AI or humans. In one case, issues arise when students heavily rely on such tools in a manner that can…

Computation and Language · Computer Science 2025-01-07 Ayat Najjar , Huthaifa I. Ashqar , Omar Darwish , Eman Hammad

The rapid advancement of large language models (LLMs) has made detecting AI-generated text an increasingly critical challenge. Traditional methods often fail to capture the nuanced semantic differences between human and machine-generated…

Computation and Language · Computer Science 2025-02-03 Lifu Gao , Ziwei Liu , Qi Zhang

ChatGPT is a conversational artificial intelligence that is a member of the generative pre-trained transformer of the large language model family. This text generative model was fine-tuned by both supervised learning and reinforcement…

Computation and Language · Computer Science 2023-06-06 Niful Islam , Debopom Sutradhar , Humaira Noor , Jarin Tasnim Raya , Monowara Tabassum Maisha , Dewan Md Farid

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

While recent advancements in the capabilities and widespread accessibility of generative language models, such as ChatGPT (OpenAI, 2022), have brought about various benefits by generating fluent human-like text, the task of distinguishing…

Computation and Language · Computer Science 2023-09-15 Mahdi Dhaini , Wessel Poelman , Ege Erdogan

The rapid development of large language models (LLMs) has significantly improved the generation of fluent and convincing text, raising concerns about their potential misuse on social media platforms. We present a comprehensive methodology…

Computation and Language · Computer Science 2025-01-22 Bryan E. Tuck , Rakesh M. Verma

There have been many recent advances in the fields of generative Artificial Intelligence (AI) and Large Language Models (LLM), with the Generative Pre-trained Transformer (GPT) model being a leading "chatbot." LLM-based chatbots have become…

Computation and Language · Computer Science 2024-08-12 Gauri Anil Godghase , Rishit Agrawal , Tanush Obili , Mark Stamp

Detecting texts generated by Large Language Models (LLMs) could cause grave mistakes due to incorrect decisions, such as undermining students' academic dignity. LLM text detection thus needs to ensure the interpretability of the decision,…

Computation and Language · Computer Science 2026-05-06 Ryuto Koike , Masahiro Kaneko , Ayana Niwa , Preslav Nakov , Naoaki Okazaki

Widely applied large language models (LLMs) can generate human-like content, raising concerns about the abuse of LLMs. Therefore, it is important to build strong AI-generated text (AIGT) detectors. Current works only consider document-level…

Computation and Language · Computer Science 2023-12-18 Pengyu Wang , Linyang Li , Ke Ren , Botian Jiang , Dong Zhang , Xipeng Qiu