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Data Augmentation with Unsupervised Machine Translation Improves the Structural Similarity of Cross-lingual Word Embeddings.

, , and . ACL (student), page 163-173. Association for Computational Linguistics, (2021)

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Designing the Business Conversation Corpus., , , and . WAT@EMNLP-IJCNLP, page 54-61. Association for Computational Linguistics, (2019)Data Augmentation with Unsupervised Machine Translation Improves the Structural Similarity of Cross-lingual Word Embeddings., , and . ACL (student), page 163-173. Association for Computational Linguistics, (2021)Revisiting the Context Window for Cross-lingual Word Embeddings., and . ACL, page 995-1005. Association for Computational Linguistics, (2020)mLUKE: The Power of Entity Representations in Multilingual Pretrained Language Models., , and . CoRR, (2021)Modeling Target-side Inflection in Placeholder Translation., , and . MTSummit (1), page 231-242. Association for Machine Translation in the Americas, (2021)Pretraining with Artificial Language: Studying Transferable Knowledge in Language Models., and . ACL (1), page 7302-7315. Association for Computational Linguistics, (2022)The University of Tokyo's Submissions to the WAT 2020 Shared Task., , and . WAT@AAC/IJCNLPL, page 147-153. Association for Computational Linguistics, (2020)Designing the Business Conversation Corpus., , , and . CoRR, (2020)Document-aligned Japanese-English Conversation Parallel Corpus., , , and . WMT@EMNLP, page 639-645. Association for Computational Linguistics, (2020)Emergent Communication with Attention., , and . CogSci, cognitivesciencesociety.org, (2023)