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Masked Language Models (MLMs) have shown superior performances in numerous downstream NLP tasks when used as text encoders.
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020 · 1909
Earlier work this paper cites.
CrowS-pairs: A challenge dataset for measuring social biases in masked language models
Nikita Nangia, Clara Vania, Rasika Bhalerao, and Samuel R. Bowman. 2020 · 1967
Earlier work this paper cites.
Measuring individual differences in implicit cognition: The implicit association test
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Earlier work this paper cites.
Learning with local and global consistency
Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, and Bernhard Schölkopf. 2003 · 2003
Earlier work this paper cites.
Efficient estimation of word representation in vector space
Tomas Mikolov, Kai Chen, and Jeffrey Dean. 2013 · 2013
Earlier work this paper cites.
Ontonotes release 5.0 ldc2013t19
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Earlier work this paper cites.
Glove: global vectors for word representation
Jeffery Pennington, Richard Socher, and Christopher D. Manning. 2014 · 2014
Earlier work this paper cites.
Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books
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Earlier work this paper cites.
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Earlier work this paper cites.
Man is to computer programmer as woman is to homemaker? debiasing word embeddings
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Earlier work this paper cites.
Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
Earlier work this paper cites.
Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J. Bryson, and Arvind Narayanan. 2017 · 2017
Earlier work this paper cites.
Deep contextualized word representations
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
Earlier work this paper cites.
Gender bias in coreference resolution: Evaluation and debiasing methods
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2018a · 2018
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A typology of ethical risks in language technology with an eye towards where transparent documents can help
Emily M. Bender. 2019 · 2019
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On Measuring and Mitigating Biased Inferences of Word Embeddings
Sunipa Dev, Tao Li, Jeff Phillips, and Vivek Srikumar. 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
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The “small world of words” english word association norms for over 12,000 cue words
Simon De Deyne, Danielle J. Navarro, Amy Perfors, Marc Brysbaert, and Gert Storms. 2019 · 2019
Cited alongside, same era.
Assessing social and intersectional biases in contextualized word representations
Yi Chern Tan and L. Elisa Celis. 2019 · 2019
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BERT has a mouth, and it must speak: BERT as a Markov random field language model
Alex Wang and Kyunghyun Cho. 2019 · 2019
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Gender bias in contextualized word embeddings
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Ryan Cotterell, Vicente Ordonez, and Kai-Wei Chang. 2019 · 2019
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Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings
Rishi Bommasani, Kelly Davis, and Claire Cardie. 2020 · 2020
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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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Yupei Du, Yuanbin Wu, and Man Lan. 2019 · 2019
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Understanding undesirable word embedding associations
Kawin Ethayarajh, David Duvenaud, and Graeme Hirst. 2019 · 2019
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Conceptor debiasing of word representations evaluated on WEAT
Saket Karve, Lyle Ungar, and João Sedoc. 2019 · 2019
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Measuring bias in contextualized word representations
Keita Kurita, Nidhi Vyas, Ayush Pareek, Alan W Black, and Yulia Tsvetkov. 2019 · 2019
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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. 2019 · 2019
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Black is to criminal as caucasian is to police: Detecting and removing multiclass bias in word embeddings
Thomas Manzini, Lim Yao Chong, Alan W Black, and Yulia Tsvetkov. 2019 · 2019
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On measuring social biases in sentence encoders
Chandler May, Alex Wang, Shikha Bordia, Samuel R. Bowman, and Rachel Rudinger. 2019 · 2019
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Monolingual and multilingual reduction of gender bias in contextualized representations
Sheng Liang, Philipp Dufter, and Hinrich Schütze. 2020 · 2020
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StereoSet: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy. 2020 · 2020
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Masked language model scoring
Julian Salazar, Davis Liang, Toan Q. Nguyen, and Katrin Kirchhoff. 2020 · 2020
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Rare words: A major problem for contextualized embeddings and how to fix it by attentive mimicking
Timo Schick and Hinrich Schütze. 2020 · 2020
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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, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush. 2020 · 2020
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Debiasing pre-trained contextualised embeddings
Masahiro Kaneko and Danushka Bollegala. 2021 · 2021
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Self-diagnosis and self-debiasing: A proposal for reducing corpus-based bias in nlp
Timo Schick, Sahana Udupa, and Hinrich Schütze. 2021 · 2021
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