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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 4 of 4 1 JABER and SABER: Junior and Senior Arabic BERt ... Ghaddar, Abbas; Wu, Yimeng; Rashid, Ahmad. - : arXiv, 2021 BASE Show details 2 Extracting Parallel Sentences with Bidirectional Recurrent Neural Networks to Improve Machine Translation ... Grégoire, Francis; Langlais, Philippe. - : arXiv, 2018 Abstract: Parallel sentence extraction is a task addressing the data sparsity problem found in multilingual natural language processing applications. We propose a bidirectional recurrent neural network based approach to extract parallel sentences from collections of multilingual texts. Our experiments with noisy parallel corpora show that we can achieve promising results against a competitive baseline by removing the need of specific feature engineering or additional external resources. To justify the utility of our approach, we extract sentence pairs from Wikipedia articles to train machine translation systems and show significant improvements in translation performance. ... : 12 pages, 7 figures, COLING 2018. arXiv admin note: text overlap with arXiv:1709.09783 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG; Machine Learning stat.ML URL: https://arxiv.org/abs/1806.05559 https://dx.doi.org/10.48550/arxiv.1806.05559 BASE Hide details 3 Robust Lexical Features for Improved Neural Network Named-Entity Recognition ... Ghaddar, Abbas; Langlais, Philippe. - : arXiv, 2018 BASE Show details 4 A Deep Neural Network Approach To Parallel Sentence Extraction ... Grégoire, Francis; Langlais, Philippe. - : arXiv, 2017 BASE Show details

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