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We present two novel unsupervised methods for eliminating toxicity in text.
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. 2019 · 1907
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Disentangled representation learning for non-parallel text style transfer
Vineet John, Lili Mou, Hareesh Bahuleyan, and Olga Vechtomova. 2019 · 2019
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Multiple-attribute text rewriting
Guillaume Lample, Sandeep Subramanian, Eric Michael Smith, Ludovic Denoyer, Marc’Aurelio Ranzato, and Y-Lan Boureau. 2019 · 2019
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A dual reinforcement learning framework for unsupervised text style transfer
Fuli Luo, Peng Li, Jie Zhou, Pengcheng Yang, Baobao Chang, Xu Sun, and Zhifang Sui. 2019 · 2019
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Unsupervised evaluation metrics and learning criteria for non-parallel textual transfer
Richard Yuanzhe Pang and Kevin Gimpel. 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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"transforming" delete, retrieve, generate approach for controlled text style transfer
Akhilesh Sudhakar, Bhargav Upadhyay, and Arjun Maheswaran. 2019 · 2019
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Harnessing pre-trained neural networks with rules for formality style transfer
Yunli Wang, Yu Wu, Lili Mou, Zhoujun Li, and Wenhan Chao. 2019 · 2019
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Neural network acceptability judgments
Alex Warstadt, Amanpreet Singh, and Samuel R. Bowman. 2019 · 2019
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Beyond BLEU: training neural machine translation with semantic similarity
Reformulating unsupervised style transfer as paraphrase generation
Kalpesh Krishna, John Wieting, and Mohit Iyyer. 2020 · 2020
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Stable style transformer: Delete and generate approach with encoder-decoder for text style transfer
Joosung Lee. 2020 · 2020
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Politeness transfer: A tag and generate approach
Aman Madaan, Amrith Setlur, Tanmay Parekh, Barnabas Poczos, Graham Neubig, Yiming Yang, Ruslan Salakhutdinov, Alan W Black, and Shrimai Prabhumoye. 2020 · 2020
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Unsupervised text style transfer with padded masked language models
Eric Malmi, Aliaksei Severyn, and Sascha Rothe. 2020 · 2020
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Don’t patronize me! an annotated dataset with patronizing and condescending language towards vulnerable communities
Carla Perez Almendros, Luis Espinosa Anke, and Steven Schockaert. 2020 · 2020
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John Wieting, Taylor Berg-Kirkpatrick, Kevin Gimpel, and Graham Neubig. 2019 · 2019
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Conditional BERT contextual augmentation
Xing Wu, Shangwen Lv, Liangjun Zang, Jizhong Han, and Songlin Hu. 2019a · 2019
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Mask and infill: Applying masked language model for sentiment transfer
Xing Wu, Tao Zhang, Liangjun Zang, Jizhong Han, and Songlin Hu. 2019b · 2019
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Identifying and measuring annotator bias based on annotators’ demographic characteristics
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Plug and play language models: A simple approach to controlled text generation
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Towards non-toxic landscapes: Automatic toxic comment detection using DNN
Ashwin Geet D’Sa, Irina Illina, and Dominique Fohr. 2020 · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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Towards A friendly online community: An unsupervised style transfer framework for profanity redaction
Minh Tran, Yipeng Zhang, and Mohammad Soleymani. 2020 · 2020
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Marcos Zampieri, Preslav Nakov, Sara Rosenthal, Pepa Atanasova, Georgi Karadzhov, Hamdy Mubarak, Leon Derczynski, Zeses Pitenis, and Çağrı Çöltekin. 2020 · 2020
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Detecting inappropriate messages on sensitive topics that could harm a company’s reputation
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Toxic comment classification challenge
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Jigsaw unintended bias in toxicity classification
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Jigsaw multilingual toxic comment classification
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Civil rephrases of toxic texts with self-supervised transformers
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