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Related papers: MAGE: Machine-generated Text Detection in the Wild

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In recent years, particularly since the early 2020s, Large Language Models (LLMs) have emerged as the most powerful AI tools in addressing a diverse range of challenges, from natural language processing to complex problem-solving in various…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Xinyu Yang , Jizhe Zhou

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

In the age of large language models (LLMs) and the widespread adoption of AI-driven content creation, the landscape of information dissemination has witnessed a paradigm shift. With the proliferation of both human-written and…

Computation and Language · Computer Science 2024-04-16 Jinyan Su , Claire Cardie , Preslav Nakov

With increasing usage of generative models for text generation and widespread use of machine generated texts in various domains, being able to distinguish between human written and machine generated texts is a significant challenge. While…

Computation and Language · Computer Science 2024-10-23 Ram Mohan Rao Kadiyala

The dissemination of Large Language Models (LLMs), trained at scale, and endowed with powerful text-generating abilities, has made it easier for all to produce harmful, toxic, faked or forged content. In response, various proposals have…

Computation and Language · Computer Science 2025-06-12 Matthieu Dubois , François Yvon , Pablo Piantanida

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

The rapid advancements in large language models (LLMs) have significantly improved their ability to generate natural language, making texts generated by LLMs increasingly indistinguishable from human-written texts. While recent research has…

Computation and Language · Computer Science 2025-10-01 Sergio E. Zanotto , Segun Aroyehun

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 increasing reliance on large language models (LLMs) in academic writing has led to a rise in plagiarism. Existing AI-generated text classifiers have limited accuracy and often produce false positives. We propose a novel approach using…

Computation and Language · Computer Science 2023-06-16 Mujahid Ali Quidwai , Chunhui Li , Parijat Dube

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…

Computation and Language · Computer Science 2024-12-11 Shantanu Thorat , Tianbao Yang

The rapid advancement of Large Language Models (LLMs) has ushered in an era where AI-generated text is increasingly indistinguishable from human-generated content. Detecting AI-generated text has become imperative to combat misinformation,…

Computation and Language · Computer Science 2024-06-12 Ye Zhang , Qian Leng , Mengran Zhu , Rui Ding , Yue Wu , Jintong Song , Yulu Gong

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 models (LLMs) have revolutionized code generation, automating programming with remarkable efficiency. However, these advancements challenge programming skills, ethics, and assessment integrity, making the detection of…

Computation and Language · Computer Science 2025-07-18 Daniil Orel , Dilshod Azizov , Preslav Nakov

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,…

Computation and Language · Computer Science 2023-05-09 Evan Crothers , Nathalie Japkowicz , Herna Viktor

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…

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

The burgeoning capabilities of advanced large language models (LLMs) such as ChatGPT have led to an increase in synthetic content generation with implications across a variety of sectors, including media, cybersecurity, public discourse,…

Computation and Language · Computer Science 2023-10-25 Xianjun Yang , Liangming Pan , Xuandong Zhao , Haifeng Chen , Linda Petzold , William Yang Wang , Wei Cheng

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

Large language models can produce convincing "fake text" in domains such as academic writing, product reviews, and political news. Many approaches have been investigated for the detection of artificially generated text. While this may seem…

Computation and Language · Computer Science 2025-06-27 Andrea McGlinchey , Peter J Barclay

The recent large language models (LLMs), e.g., ChatGPT, have been able to generate human-like and fluent responses when provided with specific instructions. While admitting the convenience brought by technological advancement, educators…

Computation and Language · Computer Science 2023-12-27 Zijie Zeng , Lele Sha , Yuheng Li , Kaixun Yang , Dragan Gašević , Guanliang Chen