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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

We have witnessed lately a rapid proliferation of advanced Large Language Models (LLMs) capable of generating high-quality text. While these LLMs have revolutionized text generation across various domains, they also pose significant risks…

Computation and Language · Computer Science 2024-03-05 Tharindu Kumarage , Garima Agrawal , Paras Sheth , Raha Moraffah , Aman Chadha , Joshua Garland , Huan Liu

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

Existing tools to detect text generated by a large language model (LLM) have met with certain success, but their performance can drop when dealing with texts in new domains. To tackle this issue, we train a ranking classifier called…

Computation and Language · Computer Science 2024-10-21 You Zhou , Jie Wang

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

ChatGPT and other general large language models (LLMs) have achieved remarkable success, but they have also raised concerns about the misuse of AI-generated texts. Existing AI-generated text detection models, such as based on BERT and…

Computation and Language · Computer Science 2024-02-05 Rongsheng Wang , Haoming Chen , Ruizhe Zhou , Han Ma , Yaofei Duan , Yanlan Kang , Songhua Yang , Baoyu Fan , Tao Tan

The burgeoning progress in the field of Large Language Models (LLMs) heralds significant benefits due to their unparalleled capacities. However, it is critical to acknowledge the potential misuse of these models, which could give rise to a…

Computation and Language · Computer Science 2023-08-07 Haolan Zhan , Xuanli He , Qiongkai Xu , Yuxiang Wu , Pontus Stenetorp

With the recent proliferation of Large Language Models (LLMs), there has been an increasing demand for tools to detect machine-generated text. The effective detection of machine-generated text face two pertinent problems: First, they are…

Computation and Language · Computer Science 2024-04-04 Mazal Bethany , Brandon Wherry , Emet Bethany , Nishant Vishwamitra , Anthony Rios , Peyman Najafirad

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 demonstrated impressive capabilities in creative tasks such as storytelling and E-mail generation. However, as LLMs are primarily trained on final text results rather than intermediate revisions, it might…

Computation and Language · Computer Science 2023-12-21 Lei Shu , Liangchen Luo , Jayakumar Hoskere , Yun Zhu , Yinxiao Liu , Simon Tong , Jindong Chen , Lei Meng

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

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

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

While large language models (LLMs) exhibit significant utility across various domains, they simultaneously are susceptible to exploitation for unethical purposes, including academic misconduct and dissemination of misinformation.…

Computation and Language · Computer Science 2024-09-24 Navid Ayoobi , Lily Knab , Wen Cheng , David Pantoja , Hamidreza Alikhani , Sylvain Flamant , Jin Kim , Arjun Mukherjee

The increasing capabilities of Large Language Models (LLMs) have raised concerns about their misuse in AI-generated plagiarism and social engineering. While various AI-generated text detectors have been proposed to mitigate these risks,…

Computation and Language · Computer Science 2025-10-31 Yize Cheng , Vinu Sankar Sadasivan , Mehrdad Saberi , Shoumik Saha , Soheil Feizi

Recent advances in large language models (LLMs) have made it increasingly difficult to distinguish human-written text from AI-generated content. Many existing detectors train supervised neural classifiers that achieve strong in-distribution…

Computation and Language · Computer Science 2026-05-27 Pingfan Su , Kai Ye , Shijin Gong , Erhan Xu , Jin Zhu , Giulia Livieri , Chengchun Shi

The proliferation of large language models (LLMs) has significantly transformed the digital information landscape, making it increasingly challenging to distinguish between human-written and LLM-generated content. Detecting LLM-generated…

Computation and Language · Computer Science 2025-06-30 Minjia Mao , Dongjun Wei , Xiao Fang , Michael Chau

The ease of access to large language models (LLMs) has enabled a widespread of machine-generated texts, and now it is often hard to tell whether a piece of text was human-written or machine-generated. This raises concerns about potential…

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

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