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We have witnessed lately a rapid proliferation of advanced Large Language Models (LLMs) capable of generating high-quality text.
Real or fake? learning to discriminate machine from human generated text
Anton Bakhtin, Sam Gross, Myle Ott, Yuntian Deng, Marc’Aurelio Ranzato, and Arthur Szlam. 2019 · 1906
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GLTR: Statistical Detection and Visualization of Generated Text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander M. Rush. 2019 · 1906
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Release strategies and the social impacts of language models
Irene Solaiman, Miles Brundage, Jack Clark, Amanda Askell, Ariel Herbert-Voss, Jeff Wu, Alec Radford, Gretchen Krueger, Jong Wook Kim, Sarah Kreps, et al. 2019 · 1908
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Automatic detection of generated text is easiest when humans are fooled
Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, and Douglas Eck. 2019 · 1911
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A mathematical theory of communication
Claude Elwood Shannon. 1948 · 1948
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A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, and Pascal Vincent. 2000 · 2000
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Computational methods in authorship attribution
Moshe Koppel, Jonathan Schler, and Shlomo Argamon. 2009 · 2009
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Causality
Judea Pearl. 2009 · 2009
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Source code authorship attribution using long short-term memory based networks
Bander Alsulami et al. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Experiments with convolutional neural networks for multi-label authorship attribution
Dainis Boumber, Yifan Zhang, and Arjun Mukherjee. 2018 · 2018
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 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 · 2019
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Generating sentiment-preserving fake online reviews using neural language models and their human-and machine-based detection
David Ifeoluwa Adelani, Haotian Mai, Fuming Fang, Huy H Nguyen, Junichi Yamagishi, and Isao Echizen. 2020 · 2020
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Automatic detection of generated text is easiest when humans are fooled
Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, and Douglas Eck. 2020 · 2020
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Automatic detection of machine generated text: A critical survey
Ganesh Jawahar, Muhammad Abdul-Mageed, and VS Laks Lakshmanan. 2020 · 2020
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Authorship attribution for neural text generation
Adaku Uchendu, Thai Le, Kai Shu, and Dongwon Lee. 2020 · 2020
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Defending against neural fake news
Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, and Yejin Choi. 2020 · 2020
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Neural deepfake detection with factual structure of text
Wanjun Zhong, Duyu Tang, Zenan Xu, Ruize Wang, Nan Duan, Ming Zhou, Jiahai Wang, and Jian Yin. 2020 · 2020
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Tweepfake: About detecting deepfake tweets
Tiziano Fagni, Fabrizio Falchi, Margherita Gambini, Antonio Martella, and Maurizio Tesconi. 2021 · 2021
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Artificial text detection via examining the topology of attention maps
Laida Kushnareva, Daniil Cherniavskii, Vladislav Mikhailov, Ekaterina Artemova, Serguei Barannikov, Alexander Bernstein, Irina Piontkovskaya, Dmitri Piontkovski, and Evgeny Burnaev. 2021a · 2021
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All the news that’s fit to fabricate: Ai-generated text as a tool of media misinformation
Sarah Kreps, R Miles McCain, and Miles Brundage. 2022 · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
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Visualizing and reasoning about presentable digital forensic evidence with knowledge graphs
Weifeng Xu and Dianxiang Xu. 2022 · 2022
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Can knowledge graphs reduce hallucinations in llms?: A survey
Garima Agrawal, Tharindu Kumarage, Zeyad Alghami, and Huan Liu. 2023 · 2023
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Gpt-2 versus gpt-3 and bloom: Llms for llms generative text detection
Fernando Aguilar-Canto, Marco Cardoso-Moreno, Diana Jiménez, and Hiram Calvo. 2023 · 2023
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The falcon series of open language models
Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, Alessandro Cappelli, Ruxandra Cojocaru, Mérouane Debbah, Étienne Goffinet, Daniel Hesslow, Julien Launay, Quentin Malartic, et al. 2023 · 2023
Earlier work this paper cites.
Guangsheng Bao, Yanbin Zhao, Zhiyang Teng, Linyi Yang, and Yue Zhang. 2023 · 2023
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Fighting Fire with Fire: Can ChatGPT Detect AI-generated Text?
Amrita Bhattacharjee and Huan Liu. 2023 · 2023
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Can llm-generated misinformation be detected?
Canyu Chen and Kai Shu. 2023 · 2023
Cited alongside, same era.
Do models explain themselves? counterfactual simulatability of natural language explanations
Yanda Chen, Ruiqi Zhong, Narutatsu Ri, Chen Zhao, He He, Jacob Steinhardt, Zhou Yu, and Kathleen McKeown. 2023 · 2023
Cited alongside, same era.
Stadee: Statistics-based deep detection of machine generated text
Zheng Chen and Huming Liu. 2023 · 2023
Cited alongside, same era.
Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E Gonzalez, et al. 2023 · 2023
Cited alongside, same era.
LM vs LM: Detecting Factual Errors via Cross Examination
Roi Cohen, May Hamri, Mor Geva, and Amir Globerson. 2023 · 2023
Language model detectors are easily optimized against
Charlotte Nicks, Eric Mitchell, Rafael Rafailov, Archit Sharma, Christopher D Manning, Chelsea Finn, and Stefano Ermon. 2023 · 2023
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OpenAI. 2023 · 2023
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On the risk of misinformation pollution with large language models
Yikang Pan, Liangming Pan, Wenhu Chen, Preslav Nakov, Min-Yen Kan, and William Yang Wang. 2023 · 2023
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Generative agents: Interactive simulacra of human behavior
Joon Sung Park, Joseph O’Brien, Carrie Jun Cai, Meredith Ringel Morris, Percy Liang, and Michael S Bernstein. 2023 · 2023
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To chatgpt, or not to chatgpt: That is the question!
Alessandro Pegoraro, Kavita Kumari, Hossein Fereidooni, and Ahmad-Reza Sadeghi. 2023 · 2023
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Cited alongside, same era.
Machine-generated text: A comprehensive survey of threat models and detection methods
Evan Crothers, Nathalie Japkowicz, and Herna L Viktor. 2023 · 2023
Cited alongside, same era.
Who said that? benchmarking social media ai detection
Wanyun Cui, Linqiu Zhang, Qianle Wang, and Shuyang Cai. 2023 · 2023
Cited alongside, same era.
Detecting AI Authorship: Analyzing Descriptive Features for AI Detection
Helene F. L. Eriksen, Christopher M. J. André, Emil J. Jakobsen, Luca C. B. Mingolla, and Nicolai B. Thomsen. 2023 · 2023
Cited alongside, same era.
Matching pairs: Attributing fine-tuned models to their pre-trained large language models
Myles Foley et al. 2023 · 2023
Cited alongside, same era.
A prompt in the right direction: Prompt based classification of machine-generated text detection
Rinaldo Gagiano and Lin Tian. 2023 · 2023
Cited alongside, same era.
Detecting generated text and attributing language model source with fine-tuned models and semantic understanding
Margherita Gambini, Marco Avvenuti, Fabrizio Falchi, Maurizio Tesconi, and Tiziano Fagni. 2023 · 2023
Cited alongside, same era.
The false promise of imitating proprietary llms
Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, and Dawn Song. 2023 · 2023
Cited alongside, same era.
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A Robust Semantics-based Watermark for Large Language Model against Paraphrasing
Jie Ren, Han Xu, Yiding Liu, Yingqian Cui, Shuaiqiang Wang, Dawei Yin, and Jiliang Tang. 2023 · 2023
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Can AI-Generated Text be Reliably Detected?
Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, Wenxiao Wang, and Soheil Feizi. 2023 · 2023
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Areg Mikael Sarvazyan, José Ángel González, Marc Franco-Salvador, Francisco Rangel, Berta Chulvi, and Paolo Rosso. 2023a · 2023
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Ai model gpt-3 (dis)informs us better than humans
Giovanni Spitale, Nikola Biller-Andorno, and Federico Germani. 2023 · 2023
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Towards detecting harmful agendas in news articles
Melanie Subbiah, Amrita Bhattacharjee, Yilun Hua, Tharindu Kumarage, Huan Liu, and Kathleen McKeown. 2023 · 2023
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The science of detecting llm-generated texts
Ruixiang Tang, Yu-Neng Chuang, and Xia Hu. 2023 · 2023
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Alpaca: A strong, replicable instruction-following model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B Hashimoto. 2023 · 2023
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Gemini: a family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, , et al. 2023 · 2023
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Hansen: human and ai spoken text benchmark for authorship analysis
Nafis Irtiza Tripto, Adaku Uchendu, Thai Le, Mattia Setzu, Fosca Giannotti, and Dongwon Lee. 2023 · 2023
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Attribution and obfuscation of neural text authorship: A data mining perspective
Adaku Uchendu, Thai Le, and Dongwon Lee. 2023 · 2023
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GPT-who: An Information Density-based Machine-Generated Text Detector
Saranya Venkatraman, Adaku Uchendu, and Dongwon Lee. 2023 · 2023
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Fake news in sheep’s clothing: Robust fake news detection against llm-empowered style attacks
Jiaying Wu and Bryan Hooi. 2023 · 2023
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Llmdet: A third party large language models generated text detection tool
Kangxi Wu, Liang Pang, Huawei Shen, Xueqi Cheng, and Tat-Seng Chua. 2023 · 2023
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Mfd: Multi-feature detection of llm-generated text
Zhendong Wu and Hui Xiang. 2023 · 2023
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Anatomy of an ai-powered malicious social botnet
Kai-Cheng Yang and Filippo Menczer. 2023 · 2023
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Is chatgpt involved in texts? measure the polish ratio to detect chatgpt-generated text
Lingyi Yang, Feng Jiang, and Haizhou Li. 2023 · 2023
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A knowledge graph question answering approach to iot forensics
Ruipeng Zhang and Mengjun Xie. 2023 · 2023
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Synthetic lies: Understanding ai-generated misinformation and evaluating algorithmic and human solutions
Jiawei Zhou, Yixuan Zhang, Qianni Luo, Andrea G Parker, and Munmun De Choudhury. 2023 · 2023
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Beat LLMs at Their Own Game: Zero-Shot LLM-Generated Text Detection via Querying ChatGPT
Biru Zhu, Lifan Yuan, Ganqu Cui, Yangyi Chen, Chong Fu, Bingxiang He, Yangdong Deng, Zhiyuan Liu, Maosong Sun, and Ming Gu. 2023 · 2023
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Comparing the willingness to share for human-generated vs. ai-generated fake news
Amirsiavosh Bashardoust, Stefan Feuerriegel, and Yash Raj Shrestha. 2024 · 2024
Closest in time.
How persuasive is ai-generated propaganda?
Josh A Goldstein, Jason Chao, Shelby Grossman, Alex Stamos, and Michael Tomz. 2024 · 2024
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A Survey of Text Watermarking in the Era of Large Language Models
Aiwei Liu, Leyi Pan, Yijian Lu, Jingjing Li, Xuming Hu, Lijie Wen, Irwin King, and Philip S. Yu. 2024 · 2024
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