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Transformer based models are the modern work horses for neural machine translation (NMT), reaching state of the art across several benchmarks.
On binding
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Binding theory
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Beyond english-centric multilingual machine translation
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Astraea: Grammar-based fairness testing
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chrF: character n-gram f-score for automatic MT evaluation
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Man is to computer programmer as woman is to homemaker? debiasing word embeddings
Tolga Bolukbasi, Kai-Wei Chang, James Y Zou, Venkatesh Saligrama, and Adam T Kalai. 2016 · 2016
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Tree-to-sequence attentional neural machine translation
Akiko Eriguchi, Kazuma Hashimoto, and Yoshimasa Tsuruoka. 2016 · 2016
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The social impact of natural language processing
Dirk Hovy and Shannon L Spruit. 2016 · 2016
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Anaphora and semantic interpretation
Tanya Reinhart. 2016 · 2016
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Towards string-to-tree neural machine translation
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Syntactic and cognitive issues in investigating gendered coreference
Lauren Ackerman. 2019 · 2019
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Is man the measure of all things? a social cognitive account of androcentrism
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Automatically extracting challenge sets for non-local phenomena in neural machine translation
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Women’s syntactic resilience and men’s grammatical luck: Gender-bias in part-of-speech tagging and dependency parsing
Aparna Garimella, Carmen Banea, Dirk Hovy, and Rada Mihalcea. 2019 · 2019
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Lipstick on a pig: Debiasing methods cover up systematic gender biases in word embeddings but do not remove them
Hila Gonen and Yoav Goldberg. 2019 · 2019
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Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J Bryson, and Arvind Narayanan. 2017 · 2017
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A challenge set approach to evaluating machine translation
Pierre Isabelle, Colin Cherry, and George Foster. 2017 · 2017
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Yoon Kim, Carl Denton, Luong Hoang, and Alexander M Rush. 2017 · 2017
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Social bias in elicited natural language inferences
Rachel Rudinger, Chandler May, and Benjamin Van Durme. 2017 · 2017
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Neural machine translation with extended context
Jörg Tiedemann and Yves Scherrer. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Unsupervised discovery of gendered language through latent-variable modeling
Alexander Miserlis Hoyle, Lawrence Wolf-Sonkin, Hanna Wallach, Isabelle Augenstein, and Ryan Cotterell. 2019 · 2019
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Assessing gender bias in machine translation: a case study with google translate
Marcelo OR Prates, Pedro H Avelar, and Luis C Lamb. 2019 · 2019
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Evaluating gender bias in machine translation
Gabriel Stanovsky, Noah A. Smith, and Luke Zettlemoyer. 2019 · 2019
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Findings of the 2020 conference on machine translation (WMT20)
Loïc Barrault, Magdalena Biesialska, Ondřej Bojar, Marta R. Costa-jussà, Christian Federmann, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Matthias Huck, Eric Joanis, Tom Kocmi, Philipp Koehn, Chi-kiu Lo, Nikola Ljubešić, Christof Monz, Makoto Morishita, Masaaki Nagata, Toshiaki Nakazawa, Santanu Pal, Matt Post, and Marcos Zampieri. 2020 · 2020
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Queens are powerful too: Mitigating gender bias in dialogue generation
Emily Dinan, Angela Fan, Adina Williams, Jack Urbanek, Douwe Kiela, and Jason Weston. 2020a · 2020
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Multi-dimensional gender bias classification
Emily Dinan, Angela Fan, Ledell Wu, Jason Weston, Douwe Kiela, and Adina Williams. 2020b · 2020
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Type B reflexivization as an unambiguous testbed for multilingual multi-task gender bias
Ana Valeria González, Maria Barrett, Rasmus Hvingelby, Kellie Webster, and Anders Søgaard. 2020 · 2020
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Stanza: A python natural language processing toolkit for many human languages
Peng Qi, Yuhao Zhang, Yuhui Zhang, Jason Bolton, and Christopher D. Manning. 2020 · 2020
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OPUS-MT – building open translation services for the world
Jörg Tiedemann and Santhosh Thottingal. 2020 · 2020
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Word alignment by fine-tuning embeddings on parallel corpora
Zi-Yi Dou and Graham Neubig. 2021 · 2021
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