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Recent progress in generative language models has enabled machines to generate astonishingly realistic texts.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
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Cross-lingual language model pretraining
Guillaume Lample and Alexis Conneau. 2019 · 1901
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Fake news detection via nlp is vulnerable to adversarial attacks
Zhixuan Zhou, Huankang Guan, Meghana Moorthy Bhat, and Justin Hsu. 2019 · 1901
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Syntactic recurrent neural network for authorship attribution
Fereshteh Jafariakinabad, Sansiri Tarnpradab, and Kien A Hua. 2019 · 1902
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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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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019b · 1907
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Facebook fair’s wmt19 news translation task submission
Nathan Ng, Kyra Yee, Alexei Baevski, Myle Ott, Michael Auli, and Sergey Edunov. 2019 · 1907
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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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Ctrl: A conditional transformer language model for controllable generation
Nitish Shirish Keskar, Bryan McCann, Lav R Varshney, Caiming Xiong, and Richard Socher. 2019 · 1909
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al. 2019 · 1910
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Eliza—a computer program for the study of natural language communication between man and machine
Joseph Weizenbaum. 1966 · 1966
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An improved topic masking technique for authorship analysis
Oren Halvani, Lukas Graner, Roey Regev, and Philipp Marquardt. 2020 · 2005
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Human or machine: Automating human likeliness evaluation of nlg texts
Erion Çano and Ondřej Bojar. 2020 · 2006
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Authorship attribution using word sequences
Rosa María Coyotl-Morales, Luis Villaseñor-Pineda, Manuel Montes-y Gómez, and Paolo Rosso. 2006 · 2006
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N-gram feature selection for authorship identification
John Houvardas and Efstathios Stamatatos. 2006 · 2006
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Neural language generation: Formulation, methods, and evaluation
Cristina Garbacea and Qiaozhu Mei. 2020 · 2007
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Person identification from text and speech genre samples
Jade Goldstein, Ransom Winder, and Roberta Sabin. 2009 · 2009
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Forensic authorship attribution using compression distances to prototypes
Maarten Lambers and Cor J Veenman. 2009 · 2009
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Computing machinery and intelligence
Alan M Turing. 2009 · 2009
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A self-supervised representation learning of sentence structure for authorship attribution
Fereshteh Jafariakinabad and Kien A Hua. 2020 · 2010
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Topic-preserving synthetic news generation: An adversarial deep reinforcement learning approach
Ahmadreza Mosallanezhad, Kai Shu, and Huan Liu. 2020 · 2010
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Local histograms of character n-grams for authorship attribution
H. Jair Escalante, Thamar Solorio, and Manuel Montes y Gómez. 2011 · 2011
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Identifying fake amazon reviews as learning from crowds
Tommaso Fornaciari and Massimo Poesio. 2014 · 2014
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Towards a general rule for identifying deceptive opinion spam
Jiwei Li, Myle Ott, Claire Cardie, and Eduard Hovy. 2014 · 2014
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Authorship identification from unstructured texts
Chunxia Zhang, Xindong Wu, Zhendong Niu, and Wei Ding. 2014 · 2014
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Not all character n-grams are created equal: A study in authorship attribution
Upendra Sapkota, Steven Bethard, Manuel Montes y Gomez, and Thamar Solorio. 2015 · 2015
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Authorship attribution using a neural network language model
Zhenhao Ge, Yufang Sun, and Mark Smith. 2016 · 2016
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Neural text generation from structured data with application to the biography domain
Rémi Lebret, David Grangier, and Michael Auli. 2016 · 2016
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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Domain adaptation for authorship attribution: Improved structural correspondence learning
Gltr: Statistical detection and visualization of generated text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander M Rush. 2019 · 2019
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Style-aware neural model with application in authorship attribution
Fereshteh Jafariakinabad and Kien A Hua. 2019 · 2019
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A girl has no name: Automated authorship obfuscation using mutant-x
Asad Mahmood, Faizan Ahmad, Zubair Shafiq, Padmini Srinivasan, and Fareed Zaffar. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Do massively pretrained language models make better storytellers?
Abigail See, Aneesh Pappu, Rohun Saxena, Akhila Yerukola, and Christopher D Manning. 2019 · 2019
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Characterizing man-made vs. machine-made chatbot dialogs
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Upendra Sapkota, Thamar Solorio, Manuel Montes y Gomez, and Steven Bethard. 2016 · 2016
Cited alongside, same era.
Leveraging discourse information effectively for authorship attribution
Elisa Ferracane, Su Wang, and Raymond Mooney. 2017 · 2017
Cited alongside, same era.
Authorship attribution with convolutional neural networks and pos-eliding
Julian Hitschler, Esther Van Den Berg, and Ines Rehbein. 2017 · 2017
Cited alongside, same era.
Assessing the stylistic properties of neurally generated text in authorship attribution
Enrique Manjavacas, Jeroen De Gussem, Walter Daelemans, and Mike Kestemont. 2017 · 2017
Cited alongside, same era.
Truth of varying shades: Analyzing language in fake news and political fact-checking
Hannah Rashkin, Eunsol Choi, Jin Yea Jang, Svitlana Volkova, and Yejin Choi. 2017 · 2017
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Convolutional neural networks for authorship attribution of short texts
Prasha Shrestha, Sebastian Sierra, Fabio Gonzalez, Manuel Montes, Paolo Rosso, and Thamar Solorio. 2017 · 2017
Cited alongside, same era.
Fake news detection on social media: A data mining perspective
Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, and Huan Liu. 2017 · 2017
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Adaku Uchendu, Jeffery Cao, Qiaozhi Wang, Bo Luo, and Dongwon Lee. 2019 · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Russ R Salakhutdinov, and Quoc V Le. 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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How effectively can machines defend against machine-generated fake news? an empirical study
Meghana Moorthy Bhat and Srinivasan Parthasarathy. 2020 · 2020
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Facebook ai’s wmt20 news translation task submission
Peng-Jen Chen, Ann Lee, Changhan Wang, Naman Goyal, Angela Fan, Mary Williamson, and Jiatao Gu. 2020 · 2020
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Plug and play language models: A simple approach to controlled text generation
Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, and Rosanne Liu. 2020 · 2020
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Bertaa: Bert fine-tuning for authorship attribution
Maël Fabien, Esa ú Villatoro-Tello, Petr Motlicek, and Shantipriya Parida. 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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Early author profiling on twitter using profile features with multi-resolution
A Pastor López-Monroy, Fabio A González, and Thamar Solorio. 2020 · 2020
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The limitations of stylometry for detecting machine-generated fake news
Tal Schuster, Roei Schuster, Darsh J Shah, and Regina Barzilay. 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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Limits of detecting text generated by large-scale language models
Lav R Varshney, Nitish Shirish Keskar, and Richard Socher. 2020 · 2020
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Dialogpt: Large-scale generative pre-training for conversational response generation
Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, and William B Dolan. 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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Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity
William Fedus, Barret Zoph, and Noam Shazeer. 2021 · 2021
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Through the looking glass: Learning to attribute synthetic text generated by language models
Shaoor Munir, Brishna Batool, Zubair Shafiq, Padmini Srinivasan, and Fareed Zaffar. 2021 · 2021
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Fact-enhanced synthetic news generation
Kai Shu, Yichuan Li, Kaize Ding, and Huan Liu. 2021 · 2021
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