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The rapid development of autoregressive Large Language Models (LLMs) has significantly improved the quality of generated texts, necessitating reliable machine-generated text detectors. A huge number of detectors and collections with AI…

Computation and Language · Computer Science 2025-03-10 German Gritsai , Anastasia Voznyuk , Andrey Grabovoy , Yury Chekhovich

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…

Computation and Language · Computer Science 2025-01-20 Vinu Sankar Sadasivan , Aounon Kumar , Sriram Balasubramanian , Wenxiao Wang , Soheil Feizi

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…

With the development of large language models (LLMs), detecting whether text is generated by a machine becomes increasingly challenging in the face of malicious use cases like the spread of false information, protection of intellectual…

Computation and Language · Computer Science 2024-04-03 Ying Zhou , Ben He , Le Sun

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 demonstrated remarkable capabilities in generating text that closely resembles human writing across a wide range of styles and genres. However, such capabilities are prone to potential misuse, such as fake…

Computation and Language · Computer Science 2025-05-20 Harika Abburi , Sanmitra Bhattacharya , Edward Bowen , Nirmala Pudota

Our work addresses the critical issue of distinguishing text generated by Large Language Models (LLMs) from human-produced text, a task essential for numerous applications. Despite ongoing debate about the feasibility of such…

Computation and Language · Computer Science 2023-10-04 Souradip Chakraborty , Amrit Singh Bedi , Sicheng Zhu , Bang An , Dinesh Manocha , Furong Huang

Recent Large Language Models (LLMs) have demonstrated remarkable capabilities in generating text that closely resembles human writing across wide range of styles and genres. However, such capabilities are prone to potential abuse, such as…

Computation and Language · Computer Science 2023-11-09 Harika Abburi , Kalyani Roy , Michael Suesserman , Nirmala Pudota , Balaji Veeramani , Edward Bowen , Sanmitra Bhattacharya

The widespread adoption of Large Language Models (LLMs) has made the detection of AI-Generated text a pressing and complex challenge. Although many detection systems report high benchmark accuracy, their reliability in real-world settings…

Computation and Language · Computer Science 2026-04-23 Shushanta Pudasaini , Luis Miralles-Pechuán , David Lillis , Marisa Llorens Salvador

Detecting AI-generated text is a difficult problem to begin with; detecting AI-generated text on social media is made even more difficult due to the short text length and informal, idiosyncratic language of the internet. It is nonetheless…

Computation and Language · Computer Science 2025-06-17 Hillary Dawkins , Kathleen C. Fraser , Svetlana Kiritchenko

The rapid progress of large language models has enabled the generation of text that closely resembles human writing, creating challenges for authenticity verification in education, publishing, and digital security. Detecting AI-generated…

Computation and Language · Computer Science 2026-01-29 Michał Gromadzki , Anna Wróblewska , Agnieszka Kaliska

The growing use of large language models (LLMs) for text generation has led to widespread concerns about AI-generated content detection. However, an overlooked challenge is AI-polished text, where human-written content undergoes subtle…

Computation and Language · Computer Science 2025-05-06 Shoumik Saha , Soheil Feizi

Large language models (LLMs) present significant risks when used to generate non-factual content and spread disinformation at scale. Detecting such LLM-generated content is crucial, yet current detectors often struggle to generalize in…

Computation and Language · Computer Science 2025-02-18 Ran Li , Wei Hao , Weiliang Zhao , Junfeng Yang , Chengzhi Mao

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

To combat the misuse of Large Language Models (LLMs), many recent studies have presented LLM-generated-text detectors with promising performance. When users instruct LLMs to generate texts, the instruction can include different constraints…

Computation and Language · Computer Science 2024-10-02 Ryuto Koike , Masahiro Kaneko , Naoaki Okazaki

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…

Computation and Language · Computer Science 2026-03-05 Jiangang Hao

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 widespread use of human-like text from Large Language Models (LLMs) necessitates the development of robust detection systems. However, progress is limited by a critical lack of suitable training data; existing datasets are often…

Computation and Language · Computer Science 2025-09-26 Irina Tolstykh , Aleksandra Tsybina , Sergey Yakubson , Maksim Kuprashevich

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
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