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As advanced modern systems like deep neural networks (DNNs) and generative AI continue to enhance their capabilities in producing convincing and realistic content, the need to distinguish between user-generated and machine generated content is becoming increasingly evident.
Readability formulas: Useful or useless?
Glenda M. McCLURE · 1987
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Linguistic models for analyzing and detecting biased language
Marta Recasens, Cristian Danescu-Niculescu-Mizil, and Dan Jurafsky · 2013
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Generating sentiment-preserving fake online reviews using neural language models and their human- and machine-based detection
David Ifeoluwa Adelani, Hao Thi Mai, Fuming Fang, Huy Hoang Nguyen, Junichi Yamagishi, and Isao Echizen · 2019
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Gltr: Statistical detection and visualization of generated text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander M. Rush · 2019
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Robust fake news detection over time and attack
Benjamin D Horne, Jeppe Nørregaard, and Sibel Adali · 2019
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Irene Solaiman, Miles Brundage, Jack Clark, Amanda Askell, Ariel Herbert-Voss, Jeff Wu, Alec Radford, and Jasmine Wang · 2019
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Defending against neural fake news
Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, and Yejin Choi · 2019
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Automatic detection of machine generated text: A critical survey
Ganesh Jawahar, Muhammad Abdul-Mageed, and Laks V. S. Lakshmanan · 2020
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Detecting bot-generated text by characterizing linguistic accommodation in human-bot interactions
Paras Bhatt and Anthony Rios · 2021
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All that’s ‘human’ is not gold: Evaluating human evaluation of generated text
Elizabeth Clark, Tal August, Sofia Serrano, Nikita Haduong, Suchin Gururangan, and Noah A. Smith · 2021
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Threat scenarios and best practices to detect neural fake news
Artidoro Pagnoni, Martin Graciarena, and Yulia Tsvetkov · 2022
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Cross-domain detection of GPT-2-generated technical text
Juan Diego Rodriguez, Todd Hay, David Gros, Zain Shamsi, and Ravi Srinivasan · 2022
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Large linguistic models: Analyzing theoretical linguistic abilities of llms, 2023
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Abstracts written by ChatGPT fool scientists
Holly Else · 2023
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Michael Elsen-Rooney · 2023
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Robin A Emsley · 2023
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Biyang Guo, Xin Zhang, Ziyuan Wang, Minqi Jiang, Jinran Nie, Yuxuan Ding, Jianwei Yue, and Yupeng Wu · 2023
Chatgpt or human? detect and explain. explaining decisions of machine learning model for detecting short chatgpt-generated text, 2023
Sandra Mitrović, Davide Andreoletti, and Omran Ayoub · 2023
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Artificial intelligence implications for academic cheating: Expanding the dimensions of responsible human-ai collaboration with chatgpt and bard
Jo Ann Oravec · 2023
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Large Language Model Advanced Data Analysis Abuse to Create a Fake Data Set in Medical Research
Andrea Taloni, Vincenzo Scorcia, and Giuseppe Giannaccare · 2023
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The science of detecting llm-generated texts, 2023
Ruixiang Tang, Yu-Neng Chuang, and Xia Hu · 2023
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Gpt-4 can ace the bar, but it only has a decent chance of passing the cfa exams. here’s a list of difficult exams the chatgpt and gpt-4 have passed., Nov 2023
Lakshmi Varanasi · 2023
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The use of large language models to generate education materials about uveitis
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Assessing the strengths and weaknesses of large language models
Shalom Lappin · 2023
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Large language models understand and can be enhanced by emotional stimuli, 2023
Cheng Li, Jindong Wang, Yixuan Zhang, Kaijie Zhu, Wenxin Hou, Jianxun Lian, Fang Luo, Qiang Yang, and Xing Xie · 2023
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Differentiate chatgpt-generated and human-written medical texts, 2023
Wenxiong Liao, Zhengliang Liu, Haixing Dai, Shaochen Xu, Zihao Wu, Yiyang Zhang, Xiaoke Huang, Dajiang Zhu, Hongmin Cai, Tianming Liu, and Xiang Li · 2023
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Chatgpt or human? detect and explain. explaining decisions of machine learning model for detecting short chatgpt-generated text, 2023
Sandra Mitrović, Davide Andreoletti, and Omran Ayoub · 2023
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Emotional intelligence of large language models, 2023
Xuena Wang, Xueting Li, Zi Yin, Yue Wu, and Liu Jia · 2023
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A survey on detection of llms-generated content
Xianjun Yang, Liangming Pan, Xuandong Zhao, Haifeng Chen, Linda Ruth Petzold, William Yang Wang, and Wei Cheng · 2023
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Cheat: A large-scale dataset for detecting chatgpt-written abstracts, 2023
Peipeng Yu, Jiahan Chen, Xuan Feng, and Zhihua Xia · 2023
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Cheat: A large-scale dataset for detecting chatgpt-written abstracts, 2023
Peipeng Yu, Jiahan Chen, Xuan Feng, and Zhihua Xia · 2023
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Number of chatgpt users, January 2024
Fabio Duarte · 2024
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Large language models: a new chapter in digital health
The Lancet Digital Health · 2024
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