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Diagnostic datasets that can detect biased models are an important prerequisite for bias reduction within natural language processing.
The Referential Reader: A Recurrent Entity Network for Anaphora Resolution
Liu, F.; Zettlemoyer, L.; and Eisenstein, J. 2019 · 1902
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SpanBERT: Improving Pre-training by Representing and Predicting Spans
Joshi, M.; Chen, D.; Liu, Y.; Weld, D. S.; Zettlemoyer, L.; and Levy, O. 2019a · 1907
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WINOGRANDE: An Adversarial Winograd Schema Challenge at Scale
Sakaguchi, K.; Bras, R. L.; Bhagavatula, C.; and Choi, Y. 2019 · 1907
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A Survey on Bias and Fairness in Machine Learning
Mehrabi, N.; Morstatter, F.; Saxena, N.; Lerman, K.; and Galstyan, A. 2019 · 1908
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More accurate tests for the statistical significance of result differences
Yeh, A. 2000 · 2000
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Data Preprocessing Techniques for Classification without Discrimination
Kamiran, F.; and Calders, T. 2012 · 2012
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Resolving Complex Cases of Definite Pronouns: The Winograd Schema Challenge
Rahman, A.; and Ng, V. 2012 · 2012
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Countering Position Bias in Instructor Interventions in MOOC Discussion Forums
Chandrasekaran, M. K.; and Kan, M.-Y. 2018 · 2018
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Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems
Kiritchenko, S.; and Mohammad, S. 2018 · 2018
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Adaptive Sensitive Reweighting to Mitigate Bias in Fairness-Aware Classification
Krasanakis, E.; Spyromitros-Xioufis, E.; Papadopoulos, S.; and Kompatsiaris, Y. 2018 · 2018
Cited alongside, same era.
Higher-Order Coreference Resolution with Coarse-to-Fine Inference
Lee, K.; He, L.; and Zettlemoyer, L. 2018 · 2018
Cited alongside, same era.
Gender Bias in Coreference Resolution
Rudinger, R.; Naradowsky, J.; Leonard, B.; and Van Durme, B. 2018 · 2018
Cited alongside, same era.
Mind the GAP: A Balanced Corpus of Gendered Ambiguous Pronouns
Webster, K.; Recasens, M.; Axelrod, V.; and Baldridge, J. 2018 · 2018
Cited alongside, same era.
Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods
Zhao, J.; Wang, T.; Yatskar, M.; Ordonez, V.; and Chang, K.-W. 2018 · 2018
Cited alongside, same era.
Syntactic and Cognitive Issues in Investigating Gendered Coreference
Ackerman, L. 2019 · 2019
BERT for Coreference Resolution: Baselines and Analysis
Joshi, M.; Levy, O.; Zettlemoyer, L.; and Weld, D. 2019b · 2019
Later among the works it cites.
WikiCREM: A Large Unsupervised Corpus for Coreference Resolution
Kocijan, V.; Camburu, O.-M.; Cretu, A.-M.; Yordanov, Y.; Blunsom, P.; and Lukasiewicz, T. 2019a · 2019
Later among the works it cites.
Improving Generalization in Coreference Resolution via Adversarial Training
Subramanian, S.; and Roth, D. 2019 · 2019
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Mitigating Gender Bias in Natural Language Processing: Literature Review
Sun, T.; Gaut, A.; Tang, S.; Huang, Y.; ElSherief, M.; Zhao, J.; Mirza, D.; Belding, E.; Chang, K.-W.; and Wang, W. Y. 2019 · 2019
Later among the works it cites.
Gendered Ambiguous Pronoun (GAP) Shared Task at the Gender Bias in NLP Workshop 2019
Webster, K.; Costa-jussà, M. R.; Hardmeier, C.; and Radford, W. 2019 · 2019
Later among the works it cites.
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Cited alongside, same era.
Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting
De-Arteaga, M.; Romanov, A.; Wallach, H.; Chayes, J.; Borgs, C.; Chouldechova, A.; Geyik, S.; Kenthapadi, K.; and Kalai, A. T. 2019 · 2019
Cited alongside, same era.
The KnowRef Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution
Emami, A.; Trichelair, P.; Trischler, A.; Suleman, K.; Schulz, H.; and Cheung, J. C. K. 2019 · 2019
Cited alongside, same era.
A Surprisingly Robust Trick for the Winograd Schema Challenge
Kocijan, V.; Cretu, A.-M.; Camburu, O.-M.; Yordanov, Y.; and Lukasiewicz, T. 2019b
Cited in the paper.
Dev, S.; Li, T.; Phillips, J. M.; and Srikumar, V. 2020 · 2020
Closest in time.
Identifying and Correcting Label Bias in Machine Learning
Jiang, H.; and Nachum, O. 2020 · 2020
Closest in time.
Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection
Ravfogel, S.; Elazar, Y.; Gonen, H.; Twiton, M.; and Goldberg, Y. 2020 · 2020
Closest in time.