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Embedding Learning Through Multilingual Concept Induction.

, , , , and . ACL (1), page 1520-1530. Association for Computational Linguistics, (2018)

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Static Embeddings as Efficient Knowledge Bases?, , and . NAACL-HLT, page 2353-2363. Association for Computational Linguistics, (2021)Identifying Elements Essential for BERT's Multilinguality., and . EMNLP (1), page 4423-4437. Association for Computational Linguistics, (2020)Subword Sampling for Low Resource Word Alignment., , , , and . CoRR, (2020)Analytical Methods for Interpretable Ultradense Word Embeddings., and . EMNLP/IJCNLP (1), page 1185-1191. Association for Computational Linguistics, (2019)SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings., , and . CoRR, (2020)An Information-Theoretic Approach and Dataset for Probing Gender Stereotypes in Multilingual Masked Language Models., , , and . NAACL-HLT (Findings), page 921-932. Association for Computational Linguistics, (2022)Increasing Learning Efficiency of Self-Attention Networks through Direct Position Interactions, Learnable Temperature, and Convoluted Attention., , and . COLING, page 3630-3636. International Committee on Computational Linguistics, (2020)Embedding Learning Through Multilingual Concept Induction., , , , and . ACL (1), page 1520-1530. Association for Computational Linguistics, (2018)A Universal Semantic Space., and . CoRR, (2018)Graph Algorithms for Multiparallel Word Alignment., , , , , and . EMNLP (1), page 8457-8469. Association for Computational Linguistics, (2021)