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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

Large language models (LLMs) have advanced to a point that even humans have difficulty discerning whether a text was generated by another human, or by a computer. However, knowing whether a text was produced by human or artificial…

Computation and Language · Computer Science 2025-04-15 Kathleen C. Fraser , Hillary Dawkins , Svetlana Kiritchenko

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

Large Language Models (LLMs) have revolutionized the field of Natural Language Generation (NLG) by demonstrating an impressive ability to generate human-like text. However, their widespread usage introduces challenges that necessitate…

Computation and Language · Computer Science 2024-06-28 Sara Abdali , Richard Anarfi , CJ Barberan , Jia He

Large language models (LLMs) have gained popularity in various fields for their exceptional capability of generating human-like text. Their potential misuse has raised social concerns about plagiarism in academic contexts. However,…

Human-Computer Interaction · Computer Science 2023-06-02 Luoxuan Weng , Minfeng Zhu , Kam Kwai Wong , Shi Liu , Jiashun Sun , Hang Zhu , Dongming Han , Wei Chen

Recent neural language models have taken a significant step forward in producing remarkably controllable, fluent, and grammatical text. Although studies have found that AI-generated text is not distinguishable from human-written text for…

Computation and Language · Computer Science 2023-02-14 Yongqiang Ma , Jiawei Liu , Fan Yi , Qikai Cheng , Yong Huang , Wei Lu , Xiaozhong Liu

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…

Peer review is a critical process for ensuring the integrity of published scientific research. Confidence in this process is predicated on the assumption that experts in the relevant domain give careful consideration to the merits of…

Computation and Language · Computer Science 2024-12-09 Sungduk Yu , Man Luo , Avinash Madasu , Vasudev Lal , Phillip Howard

The "Writer's Integrity" framework introduces a paradigm shift in maintaining the sanctity of human-generated text in the realms of academia, research, and publishing. This innovative system circumvents the shortcomings of current AI…

Cryptography and Security · Computer Science 2024-04-18 Sanad Aburass , Maha Abu Rumman

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 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

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

The rapid advancement of large language models (LLMs) has blurred the line between AI-generated and human-written text. This progress brings societal risks such as misinformation, authorship ambiguity, and intellectual property concerns,…

Computation and Language · Computer Science 2025-10-10 Xiaowei Zhu , Yubing Ren , Fang Fang , Qingfeng Tan , Shi Wang , Yanan Cao

Peer review is a critical process for ensuring the integrity of published scientific research. Confidence in this process is predicated on the assumption that experts in the relevant domain give careful consideration to the merits of…

Computation and Language · Computer Science 2026-02-09 Sungduk Yu , Man Luo , Avinash Madasu , Vasudev Lal , Phillip Howard

Prior studies have shown that distinguishing text generated by Large Language Models (LLMs) from human-written one is highly challenging for humans, and often no better than random guessing. To verify the generalizability of this finding…

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

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

Recent advances in generative pre-trained transformer large language models have emphasised the potential risks of unfair use of artificial intelligence (AI) generated content in an academic environment and intensified efforts in searching…

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 revolutionized text generation but also raised concerns about potential misuse, making detecting LLM-generated text (AI text) increasingly essential. While prior work has focused on…

Computation and Language · Computer Science 2025-09-30 Nafis Irtiza Tripto , Saranya Venkatraman , Mahjabin Nahar , Dongwon Lee
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