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Creating a Translation Matrix of the Bible's Names Across 591 Languages.

, , and . LREC, European Language Resources Association (ELRA), (2018)

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Evaluating Neural Machine Comprehension Model Robustness to Noisy Inputs and Adversarial Attacks., , and . CoRR, (2020)On the Robustness of Cognate Generation Models., and . LREC, page 4299-4305. European Language Resources Association, (2022)Creating a Translation Matrix of the Bible's Names Across 591 Languages., , and . LREC, European Language Resources Association (ELRA), (2018)A PhD Student's Perspective on Research in NLP in the Era of Very Large Language Models., , , , , , , , , and 12 other author(s). CoRR, (2023)The JHU Submission to the 2020 Duolingo Shared Task on Simultaneous Translation and Paraphrase for Language Education., , , , , and . NGT@ACL, page 188-197. Association for Computational Linguistics, (2020)Evaluating Neural Model Robustness for Machine Comprehension., , and . EACL, page 2470-2481. Association for Computational Linguistics, (2021)Late Fusion with Triplet Margin Objective for Multimodal Ideology Prediction and Analysis., , , and . EMNLP, page 9720-9736. Association for Computational Linguistics, (2022)An Analysis of Massively Multilingual Neural Machine Translation for Low-Resource Languages., , , , , and . LREC, page 3710-3718. European Language Resources Association, (2020)You Are What You Annotate: Towards Better Models through Annotator Representations., , , , , and . EMNLP (Findings), page 12475-12498. Association for Computational Linguistics, (2023)Creating Large-Scale Multilingual Cognate Tables., and . LREC, European Language Resources Association (ELRA), (2018)