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Perception of toxicity evolves over time and often differs between geographies and cultural backgrounds.
Electronic documents give reproducible research a new meaning
Jon F Claerbout and Martin Karrenbach · 1992
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Reproducible research in computational science
Roger D Peng · 2011
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Are you a racist or am i seeing things? annotator influence on hate speech detection on twitter
Zeerak Waseem · 2016
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Like trainer, like bot? inheritance of bias in algorithmic content moderation
Reuben Binns, Michael Veale, Max Van Kleek, and Nigel Shadbolt · 2017
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Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data
Michael Veale and Reuben Binns · 2017
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Three dimensions of reproducibility in natural language processing
K Bretonnel Cohen, Jingbo Xia, Pierre Zweigenbaum, Tiffany Callahan, Orin Hargraves, Foster Goss, Nancy Ide, Aurélie Névéol, Cyril Grouin, and Lawrence Hunter · 2018
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But who protects the moderators? the case of crowdsourced image moderation
Brandon Dang, Martin J Riedl, and Matthew Lease · 2018
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Reproducibility vs. replicability: a brief history of a confused terminology
Hans E Plesser · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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A practical taxonomy of reproducibility for machine learning research, 2018
Rachael Tatman, Jake VanderPlas, and Sohier Dane · 2018
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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 · 2019
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Racial bias in hate speech and abusive language detection datasets
Thomas Davidson, Debasmita Bhattacharya, and Ingmar Weber · 2019
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Openwebtext corpus
Aaron Gokaslan and Vanya Cohen · 2019
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Human-machine collaboration for content regulation: The case of reddit automoderator
Shagun Jhaver, Iris Birman, Eric Gilbert, and Amy Bruckman · 2019
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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
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Model cards for model reporting
Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, and Timnit Gebru · 2019
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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
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The risk of racial bias in hate speech detection
Maarten Sap, Dallas Card, Saadia Gabriel, Yejin Choi, and Noah A Smith · 2019
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Challenges in detoxifying language models
Johannes Welbl, Amelia Glaese, Jonathan Uesato, Sumanth Dathathri, John Mellor, Lisa Anne Hendricks, Kirsty Anderson, Pushmeet Kohli, Ben Coppin, and Po-Sen Huang · 2021
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al · 2022
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Reward modeling for mitigating toxicity in transformer-based language models
Farshid Faal, Ketra Schmitt, and Jia Yuan Yu · 2022
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Analyzing and addressing the difference in toxicity prediction between different comments with same semantic meaning in google’s perspective api
SK Gargee, Pranav Bhargav Gopinath, Shridhar Reddy SR Kancharla, CR Anand, and Anoop S Babu · 2022
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Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 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
Cited alongside, same era.
Realtoxicityprompts: Evaluating neural toxic degeneration in language models
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A Smith · 2020
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Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A. Smith · 2020
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Gedi: Generative discriminator guided sequence generation
Ben Krause, Akhilesh Deepak Gotmare, Bryan McCann, Nitish Shirish Keskar, Shafiq Joty, Richard Socher, and Nazneen Fatema Rajani · 2020
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GeDi: Generative discriminator guided sequence generation
Ben Krause, Akhilesh Deepak Gotmare, Bryan McCann, Nitish Shirish Keskar, Shafiq Joty, Richard Socher, and Nazneen Fatema Rajani · 2021
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DExperts: Decoding-time controlled text generation with experts and anti-experts
Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A. Smith, and Yejin Choi · 2021
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Nitesh Goyal, Ian D Kivlichan, Rachel Rosen, and Lucy Vasserman · 2022
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A new generation of perspective api: Efficient multilingual character-level transformers
Alyssa Lees, Vinh Q Tran, Yi Tay, Jeffrey Sorensen, Jai Gupta, Donald Metzler, and Lucy Vasserman · 2022
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Holistic evaluation of language models
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, et al · 2022
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Bloom: A 176b-parameter open-access multilingual language model
Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, et al · 2022
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Metadata archaeology: Unearthing data subsets by leveraging training dynamics, 2022
Shoaib Ahmed Siddiqui, Nitarshan Rajkumar, Tegan Maharaj, David Krueger, and Sara Hooker · 2022
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Shaden Smith, Mostofa Patwary, Brandon Norick, Patrick LeGresley, Samyam Rajbhandari, Jared Casper, Zhun Liu, Shrimai Prabhumoye, George Zerveas, Vijay Korthikanti, et al · 2022
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Exploring the limits of domain-adaptive training for detoxifying large-scale language models
Boxin Wang, Wei Ping, Chaowei Xiao, Peng Xu, Mostofa Patwary, Mohammad Shoeybi, Bo Li, Anima Anandkumar, and Bryan Catanzaro · 2022
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Unified detoxifying and debiasing in language generation via inference-time adaptive optimization
Zonghan Yang, Xiaoyuan Yi, Peng Li, Yang Liu, and Xing Xie · 2022
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Randomness in neural network training: Characterizing the impact of tooling
Donglin Zhuang, Xingyao Zhang, Shuaiwen Song, and Sara Hooker · 2022
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