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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

In recent years, Large Language Models (LLMs) have become integrated into our daily lives, serving as invaluable assistants in completing tasks. Widely embraced by users, the abuse of LLMs is inevitable, particularly in using them to…

Computation and Language · Computer Science 2024-05-07 Quang-Dan Tran , Van-Quan Nguyen , Quang-Huy Pham , K. B. Thang Nguyen , Trong-Hop Do

The challenge of separating AI-generated text from human-authored content is becoming more urgent as generative AI technologies like ChatGPT become more widely available. In this work, we address this issue by looking at both the detection…

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 recent proliferation of AI-generated content has prompted significant interest in developing reliable detection methods. This study explores techniques for identifying AI-generated text through sentence-level evaluation within hybrid…

Computation and Language · Computer Science 2024-12-30 Dima Galat

Recent Large Language Models (LLMs) have shown the ability to generate content that is difficult or impossible to distinguish from human writing. We investigate the ability of differently-sized LLMs to replicate human writing style in…

Computation and Language · Computer Science 2024-05-06 Tolga Buz , Benjamin Frost , Nikola Genchev , Moritz Schneider , Lucie-Aimée Kaffee , Gerard de Melo

The rapid development of large language models has led to an increase in AI-generated text, with students increasingly using LLM-generated content as their own work, which violates academic integrity. This paper presents an evaluation of AI…

Computation and Language · Computer Science 2026-01-08 Adilkhan Alikhanov , Aidar Amangeldi , Diar Demeubay , Dilnaz Akhmetzhan , Nurbek Moldakhmetov , Omar Polat , Galymzhan Zharas

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

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

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

Following the universal availability of generative AI systems with the release of ChatGPT, automatic detection of deceptive text created by Large Language Models has focused on domains such as academic plagiarism and "fake news". However,…

Computation and Language · Computer Science 2024-12-23 Andrea Cristina McGlinchey , Peter J Barclay

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. Recent research has…

Computation and Language · Computer Science 2024-12-05 Sergio E. Zanotto , Segun Aroyehun

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

It has been shown that finetuned transformers and other supervised detectors effectively distinguish between human and machine-generated text in some situations arXiv:2305.13242, but we find that even simple classifiers on top of n-gram and…

Computation and Language · Computer Science 2024-05-24 Hope McGovern , Rickard Stureborg , Yoshi Suhara , Dimitris Alikaniotis

Artificial Intelligence (AI) techniques, especially Large Language Models (LLMs), have started gaining popularity among researchers and software developers for generating source code. However, LLMs have been shown to generate code with…

Software Engineering · Computer Science 2024-11-08 Hyunjae Suh , Mahan Tafreshipour , Jiawei Li , Adithya Bhattiprolu , Iftekhar Ahmed

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…

The misuse of large language models (LLMs) poses potential risks, motivating the development of machine-generated text (MGT) detection. Existing literature primarily concentrates on binary, document-level detection, thereby neglecting texts…

Computation and Language · Computer Science 2025-06-04 Zhixiong Su , Yichen Wang , Herun Wan , Zhaohan Zhang , Minnan Luo

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 attracted considerable attention as they are capable of showcasing impressive capabilities generating comparable high-quality responses to human inputs. LLMs, can not only compose textual scripts such as…

Computational Engineering, Finance, and Science · Computer Science 2024-05-31 Denish Omondi Otieno , Faranak Abri , Sima Siami-Namini , Akbar Siami Namin

Large Language Models (LLMs), typified by OpenAI's GPT, have marked a significant advancement in artificial intelligence. Trained on vast amounts of text data, LLMs are capable of understanding and generating human-like text across a…

Artificial Intelligence · Computer Science 2024-10-29 Haochen Zhang , Yuyang Dong , Chuan Xiao , Masafumi Oyamada
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