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There are concerns that the ability of language models (LMs) to generate high quality synthetic text can be misused to launch spam, disinformation, or propaganda.
RoBERTa: A robustly optimized BERT pretraining approach
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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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Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula) for navy enlisted personnel
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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A financial service chatbot based on deep bidirectional transformers
Shi Yu, Yuxin Chen, and Hussain Zaidi. 2020 · 2003
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METEOR: An automatic metric for MT evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
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Visualizing authorship for identification
Ahmed Abbasi and Hsinchun Chen. 2006 · 2006
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Language-agnostic BERT sentence embedding
Fangxiaoyu Feng, Yinfei Yang, Daniel Cer, Naveen Arivazhagan, and Wei Wang. 2020 · 2007
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A novel approach of mining write-prints for authorship attribution in e-mail forensics
Farkhund Iqbal, Rachid Hadjidj, Benjamin CM Fung, and Mourad Debbabi. 2008 · 2008
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On the feasibility of internet-scale author identification
Arvind Narayanan, Hristo Paskov, Neil Zhenqiang Gong, John Bethencourt, Emil Stefanov, Eui Chul Richard Shin, and Dawn Song. 2012 · 2012
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Detecting authorship deception: a supervised machine learning approach using author writeprints
Lisa Pearl and Mark Steyvers. 2012 · 2012
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Learning phrase representations using RNN encoder–decoder for statistical machine translation
Kyunghyun Cho, Bart van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
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Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
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GloVe: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Jake Zhao, and Yann LeCun. 2015 · 2015
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Sebastian Ruder, Parsa Ghaffari, and John G Breslin. 2016 · 2016
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Assessing the stylistic properties of neurally generated text in authorship attribution
Enrique Manjavacas, Jeroen De Gussem, Walter Daelemans, and Mike Kestemont. 2017 · 2017
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Improving language understanding by generative pre-training (2018)
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
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A text abstraction summary model based on bert word embedding and reinforcement learning
Qicai Wang, Peiyu Liu, Zhenfang Zhu, Hongxia Yin, Qiuyue Zhang, and Lindong Zhang. 2019 · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan 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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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared 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 M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher 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 · 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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Cross-lingual language model pretraining
Alexis Conneau and Guillaume Lample. 2019 · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
GLTR: Statistical detection and visualization of generated text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander Rush. 2019 · 2019
Cited alongside, same era.
Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019 · 2019
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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 · 2019
Cited alongside, same era.
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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Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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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 Laks Lakshmanan, V.S. 2020 · 2020
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
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Privacy risks of general-purpose language models
Xudong Pan, Mi Zhang, Shouling Ji, and Min Yang. 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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An intelligent chatbot utilizing bert model and knowledge graph
SoYeop Yoo and OkRan Jeong. 2020 · 2020
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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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Sentence analogies: Exploring linguistic relationships and regularities in sentence embeddings
Xunjie Zhu and Gerard de Melo. 2020 · 2080
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