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Related papers: Detecting AI-Generated Texts in Cross-Domains

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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 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

The rise of large language models (LLMs) has created an urgent need to distinguish between human-written and LLM-generated text to ensure authenticity and societal trust. Existing detectors typically provide a binary classification for an…

Computation and Language · Computer Science 2026-05-06 Mengchu Li , Jin Zhu , Jinglai Li , Chengchun Shi

Large language models are increasingly used for many applications. To prevent illicit use, it is desirable to be able to detect AI-generated text. Training and evaluation of such detectors critically depend on suitable benchmark datasets.…

Machine Learning · Computer Science 2025-11-13 Philipp Dingfelder , Christian Riess

Large-scale conversational assistants like Alexa, Siri, Cortana and Google Assistant process every utterance using multiple models for domain, intent and named entity recognition. Given the decoupled nature of model development and large…

Computation and Language · Computer Science 2021-09-07 Rakesh Chada , Pradeep Natarajan , Darshan Fofadiya , Prathap Ramachandra

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

The remarkable capabilities and easy accessibility of large language models (LLMs) have significantly increased societal risks (e.g., fake news generation), necessitating the development of LLM-generated text (LGT) detection methods for…

Machine Learning · Computer Science 2024-11-08 Hyunseok Lee , Jihoon Tack , Jinwoo Shin

The potentials of Generative-AI technologies like Large Language models (LLMs) to revolutionize education are undermined by ethical considerations around their misuse which worsens the problem of academic dishonesty. LLMs like GPT-4 and…

Machine Learning · Computer Science 2024-07-11 Suriya Prakash Jambunathan , Ashwath Shankarnarayan , Parijat Dube

Large Language Models (LLMs) are increasingly used as "content farm" models (CFMs), to generate synthetic text that could pass for real news articles. This is already happening even for languages that do not have high-quality monolingual…

Computation and Language · Computer Science 2024-10-01 Giovanni Puccetti , Anna Rogers , Chiara Alzetta , Felice Dell'Orletta , Andrea Esuli

Large Language Models (LLMs) are now capable of generating text that closely resembles human writing, making them powerful tools for content creation, but this growing ability has also made it harder to tell whether a piece of text was…

Computation and Language · Computer Science 2025-10-21 Muhammad Ammar , Hadiya Murad Hadi , Usman Majeed Butt

Recent advances in natural language processing (NLP) may enable artificial intelligence (AI) models to generate writing that is identical to human written form in the future. This might have profound ethical, legal, and social…

Machine Learning · Computer Science 2024-04-17 Nuzhat Prova

Nowadays, powerful large language models (LLMs) such as ChatGPT have demonstrated revolutionary power in a variety of tasks. Consequently, the detection of machine-generated texts (MGTs) is becoming increasingly crucial as LLMs become more…

Cryptography and Security · Computer Science 2024-01-17 Xinlei He , Xinyue Shen , Zeyuan Chen , Michael Backes , Yang Zhang

Large Language Model (LLMs) can be used to write or modify documents, presenting a challenge for understanding the intent behind their use. For example, benign uses may involve using LLM on a human-written document to improve its grammar or…

Computation and Language · Computer Science 2025-09-22 Yitong Wang , Zhongping Zhang , Margherita Piana , Zheng Zhou , Peter Gerstoft , Bryan A. Plummer

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 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 robustness of AI-content detection models against sophisticated adversarial strategies, such as paraphrasing or word switching, is a rising concern in natural language generation (NLG) applications. This study proposes ToBlend, a novel…

Computation and Language · Computer Science 2024-10-17 Fan Huang , Haewoon Kwak , Jisun An

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

Large Language Models (LLMs), such as GPT-3 and BERT, reshape how textual content is written and communicated. These models have the potential to generate scientific content that is indistinguishable from that written by humans. Hence, LLMs…

Computation and Language · Computer Science 2024-11-19 Bushra Alhijawi , Rawan Jarrar , Aseel AbuAlRub , Arwa Bader

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

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