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1
Graph Neural Networks for Multiparallel Word Alignment ...
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CaMEL: Case Marker Extraction without Labels ...
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3
Graph Algorithms for Multiparallel Word Alignment
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing ; The 2021 Conference on Empirical Methods in Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-03424044 ; The 2021 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, Nov 2021, Punta Cana, Dominica ; https://2021.emnlp.org/ (2021)
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4
ParCourE: A Parallel Corpus Explorer for a Massively Multilingual Corpus ...
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5
Graph Algorithms for Multiparallel Word Alignment ...
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6
ParCourE: A Parallel Corpus Explorer for a Massively Multilingual Corpus ...
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7
Graph Algorithms for Multiparallel Word Alignment ...
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8
SimAlign: High Quality Word Alignments Without Parallel Training Data Using Static and Contextualized Embeddings
In: EMNLP 2020 ; https://hal.archives-ouvertes.fr/hal-03013194 ; EMNLP 2020, Association for Computational Linguistics, Nov 2020, Online, United States. pp.1627 - 1643 (2020)
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9
SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings
In: Findings of ACL: EMNLP 2020 (2020)
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10
SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings ...
Abstract: Word alignments are useful for tasks like statistical and neural machine translation (NMT) and cross-lingual annotation projection. Statistical word aligners perform well, as do methods that extract alignments jointly with translations in NMT. However, most approaches require parallel training data, and quality decreases as less training data is available. We propose word alignment methods that require no parallel data. The key idea is to leverage multilingual word embeddings, both static and contextualized, for word alignment. Our multilingual embeddings are created from monolingual data only without relying on any parallel data or dictionaries. We find that alignments created from embeddings are superior for four and comparable for two language pairs compared to those produced by traditional statistical aligners, even with abundant parallel data; e.g., contextualized embeddings achieve a word alignment F1 for English-German that is 5 percentage points higher than eflomal, a high-quality statistical ... : EMNLP (Findings) 2020 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2004.08728
https://dx.doi.org/10.48550/arxiv.2004.08728
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11
SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings ...
Sabet, Masoud Jalili; Dufter, Philipp; Schütze, Hinrich. - : Universitätsbibliothek der Ludwig-Maximilians-Universität München, 2020
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12
The Effect of Mediation via the Interventionist Model of Dynamic Assessment on Reading Comprehension: Evidence from Iranian EFL Learners
In: Journal of Education and Practice; Vol 8, No 35 (2017); 169-180 (2018)
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13
Automatic translation memory cleaning [<Journal>]
Negri, Matteo [Verfasser]; Ataman, Duygu [Sonstige]; Sabet, Masoud Jalili [Sonstige].
DNB Subject Category Language
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14
Visual and Spoken Texts in MCALL Courseware: The Effects of Text Modalities on the Vocabulary Retention of EFL Learners
In: English Language Teaching; Vol 3, No 2 (2010); P30 (2010)
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