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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

Despite the fact that large language models (LLMs) show exceptional skill in instruction following tasks, this strength can turn into a vulnerability when the models are required to disregard certain instructions. Instruction-following…

Computation and Language · Computer Science 2025-08-12 Yerin Hwang , Yongil Kim , Jahyun Koo , Taegwan Kang , Hyunkyung Bae , Kyomin Jung

Recent advancements in Large Language Models (LLMs) and their increased accessibility have made it easier than ever for students to automatically generate texts, posing new challenges for educational institutions. To enforce norms of…

Computation and Language · Computer Science 2025-08-12 Lukas Gehring , Benjamin Paaßen

Large Language Models (LLMs) have achieved human-level fluency in text generation, making it difficult to distinguish between human-written and LLM-generated texts. This poses a growing risk of misuse of LLMs and demands the development of…

Computation and Language · Computer Science 2024-02-20 Ryuto Koike , Masahiro Kaneko , Naoaki Okazaki

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 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

The increasing availability of large language models (LLMs) has raised concerns about their potential misuse in online learning. While tools for detecting LLM-generated text exist and are widely used by researchers and educators, their…

Human-Computer Interaction · Computer Science 2025-06-23 Shambhavi Bhushan , Danielle R Thomas , Conrad Borchers , Isha Raghuvanshi , Ralph Abboud , Erin Gatz , Shivang Gupta , Kenneth Koedinger

Advancements in natural language generation (NLG) and large language models (LLMs) have led to proficient text generation in various tasks. However, integrating intricate constraints into neural text generation, due to LLMs' opacity,…

Computation and Language · Computer Science 2024-03-22 Xiang Chen , Xiaojun Wan

Large Language Models (LLMs) have demonstrated a powerful ability for text generation. However, achieving optimal results with a given prompt or instruction can be challenging, especially for billion-sized models. Additionally, undesired…

Computation and Language · Computer Science 2024-10-07 Lifu Tu , Semih Yavuz , Jin Qu , Jiacheng Xu , Rui Meng , Caiming Xiong , Yingbo Zhou

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

This research investigates prompt designs of evaluating generated texts using large language models (LLMs). While LLMs are increasingly used for scoring various inputs, creating effective prompts for open-ended text evaluation remains…

Computation and Language · Computer Science 2024-06-28 KuanChao Chu , Yi-Pei Chen , Hideki Nakayama

Detecting text generated by large language models (LLMs) is of great recent interest. With zero-shot methods like DetectGPT, detection capabilities have reached impressive levels. However, the reliability of existing detectors in real-world…

Computation and Language · Computer Science 2025-03-13 Junchao Wu , Runzhe Zhan , Derek F. Wong , Shu Yang , Xinyi Yang , Yulin Yuan , Lidia S. Chao

Large language models (LLMs) have grown more powerful in language generation, producing fluent text and even imitating personal style. Yet, this ability also heightens the risk of identity impersonation. To the best of our knowledge, no…

Computation and Language · Computer Science 2026-05-01 Lang Gao , Xuhui Li , Chenxi Wang , Mingzhe Li , Wei Liu , Zirui Song , Jinghui Zhang , Rui Yan , Preslav Nakov , Xiuying Chen

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) 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

Large language models (LLMs) have transformed human writing by enhancing grammar correction, content expansion, and stylistic refinement. However, their widespread use raises concerns about authorship, originality, and ethics, even…

Computation and Language · Computer Science 2024-10-21 Zhen Tao , Zhiyu Li , Runyu Chen , Dinghao Xi , Wei Xu

Large Language Model (LLM)-based judgments leverage powerful LLMs to efficiently evaluate candidate content and provide judgment scores. However, the inherent biases and vulnerabilities of LLM-generated judgments raise concerns,…

Artificial Intelligence · Computer Science 2025-09-30 Dawei Li , Zhen Tan , Chengshuai Zhao , Bohan Jiang , Baixiang Huang , Pingchuan Ma , Abdullah Alnaibari , Kai Shu , Huan Liu

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

Large Language Models (LLMs) changed the way we design and interact with software systems. Their ability to process and extract information from text has drastically improved productivity in a number of routine tasks. Developers that want…

Machine Learning · Computer Science 2025-08-26 Federico Errica , Giuseppe Siracusano , Davide Sanvito , Roberto Bifulco

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
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