SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings - researchr publication authors

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Masoud Jalili Sabet, Philipp Dufter, François Yvon, Hinrich Schütze. SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings. In Trevor Cohn, Yulan He, Yang Liu, editors, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings, EMNLP 2020, Online Event, 16-20 November 2020. pages 1627-1643, Association for Computational Linguistics, 2020. [doi]

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