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Large language models (LM) generate remarkably fluent text and can be efficiently adapted across NLP tasks.
Nuanced metrics for measuring unintended bias with real data for text classification
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Pointer sentinel mixture models
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The LAMBADA dataset: Word prediction requiring a broad discourse context
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Measuring the Reliability of Hate Speech Annotations: The Case of the European Refugee Crisis
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Hateful symbols or hateful people? predictive features for hate speech detection on Twitter
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The problem with bias: from allocative to representational harms in machine learning. special interest group for computing
Solon Barocas, Kate Crawford, Aaron Shapiro, and Hanna Wallach. 2017 · 2017
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Thomas Davidson, Dana Warmsley, M. Macy, and Ingmar Weber. 2017 · 2017
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Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2017 · 2017
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Ex machina: Personal attacks seen at scale
Ellery Wulczyn, Nithum Thain, and Lucas Dixon. 2017 · 2017
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But who protects the moderators? the case of crowdsourced image moderation
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Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A. Smith. 2020 · 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 · 2020
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
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Reducing sentiment bias in language models via counterfactual evaluation
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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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Brandon Dang, Martin J Riedl, and Matthew Lease. 2018 · 2018
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Measuring and mitigating unintended bias in text classification
Lucas Dixon, John Li, Jeffrey Sorensen, Nithum Thain, and Lucy Vasserman. 2018 · 2018
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SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Taku Kudo and John Richardson. 2018 · 2018
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Fighting offensive language on social media with unsupervised text style transfer
Cicero Nogueira dos Santos, Igor Melnyk, and Inkit Padhi. 2018 · 2018
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Reducing gender bias in abusive language detection
Ji Ho Park, Jamin Shin, and Pascale Fung. 2018 · 2018
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Transformer-XL: Attentive language models beyond a fixed-length context
Zihang Dai, Zhilin Yang, Yiming Yang, Jaime Carbonell, Quoc Le, and Ruslan Salakhutdinov. 2019 · 2019
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Racial bias in hate speech and abusive language detection datasets
Thomas Davidson, Debasmita Bhattacharya, and Ingmar Weber. 2019 · 2019
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Automatically identifying words that can serve as labels for few-shot text classification
Timo Schick, Helmut Schmid, and Hinrich Schütze. 2020 · 2020
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Recipes for safety in open-domain chatbots
Jing Xu, Da Ju, Margaret Li, Y-Lan Boureau, Jason Weston, and Emily Dinan. 2020 · 2020
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Persistent anti-Muslim bias in large language models
Abubakar Abid, Maheen Farooqi, and James Zou. 2021 · 2021
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What we can’t measure, we can’t understand: Challenges to demographic data procurement in the pursuit of fairness
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BOLD: Dataset and metrics for measuring biases in open-ended language generation
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Self-diagnosis and self-debiasing: A proposal for reducing corpus-based bias in NLP
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The psychological well-being of content moderators
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Fairness for unobserved characteristics: Insights from technological impacts on queer communities
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Detoxifying language models risks marginalizing minority voices
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Challenges in automated debiasing for toxic language detection
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