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Bias Beyond English: Counterfactual Tests for Bias in Sentiment Analysis in Four Languages.

, , , and . ACL (Findings), page 4458-4468. Association for Computational Linguistics, (2023)

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The problem with probabilistic DAG automata for semantic graphs., , and . CoRR, (2018)Putting Human Assessments of Machine Translation Systems in Order.. WMT@NAACL-HLT, page 1-9. The Association for Computer Linguistics, (2012)978-1-937284-20-6.Pre-training on high-resource speech recognition improves low-resource speech-to-text translation., , , , and . NAACL-HLT (1), page 58-68. Association for Computational Linguistics, (2019)Word-Based Alignment, Phrase-Based Translation: What's the Link?, and . AMTA, page 90-99. Association for Machine Translation in the Americas, (2006)Low-Rank Softmax Can Have Unargmaxable Classes in Theory but Rarely in Practice., , and . ACL (1), page 6738-6758. Association for Computational Linguistics, (2022)Understanding Learning Dynamics Of Language Models with SVCCA., and . CoRR, (2018)Universal Dependencies to Logical Forms with Negation Scope., , , and . CoRR, (2017)Detecting negation scope is easy, except when it isn't., , , and . EACL (2), page 58-63. Association for Computational Linguistics, (2017)Translation as Weighted Deduction.. EACL, page 532-540. The Association for Computer Linguistics, (2009)What do character-level models learn about morphology? The case of dependency parsing., , and . EMNLP, page 2573-2583. Association for Computational Linguistics, (2018)