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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 Page: 1 2 Hits 1 – 20 of 32 1 Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine Translation ... Jiao, Wenxiang; Wang, Xing; Tu, Zhaopeng; Shi, Shuming; Lyu, Michael R.; King, Irwin. - : arXiv, 2021 Abstract: Self-training has proven effective for improving NMT performance by augmenting model training with synthetic parallel data. The common practice is to construct synthetic data based on a randomly sampled subset of large-scale monolingual data, which we empirically show is sub-optimal. In this work, we propose to improve the sampling procedure by selecting the most informative monolingual sentences to complement the parallel data. To this end, we compute the uncertainty of monolingual sentences using the bilingual dictionary extracted from the parallel data. Intuitively, monolingual sentences with lower uncertainty generally correspond to easy-to-translate patterns which may not provide additional gains. Accordingly, we design an uncertainty-based sampling strategy to efficiently exploit the monolingual data for self-training, in which monolingual sentences with higher uncertainty would be sampled with higher probability. Experimental results on large-scale WMT English$\Rightarrow$German and ... : ACL 2021 main conference, long paper, 11 pages ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Information Theory cs.IT URL: https://dx.doi.org/10.48550/arxiv.2106.00941 https://arxiv.org/abs/2106.00941 BASE Hide details 2 Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine Translation ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Jiao, Wenxiang; King, Irwin. - : Underline Science Inc., 2021 BASE Show details 3 On the Copying Behaviors of Pre-Training for Neural Machine Translation ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Chao, Lidia S.; Ding, Liang. - : Underline Science Inc., 2021 BASE Show details 4 Multi-Task Learning with Shared Encoder for Non-Autoregressive Machine Translation ... Hao, Yongchang; He, Shilin; Jiao, Wenxiang. - : arXiv, 2020 BASE Show details 5 On the Inference Calibration of Neural Machine Translation ... Wang, Shuo; Tu, Zhaopeng; Shi, Shuming. - : arXiv, 2020 BASE Show details 6 EmpDG: Multi-resolution Interactive Empathetic Dialogue Generation ... The 28th International Conference on Computational Linguistics 2020; Chen , Hongshen; Chen , Zhumin. - : Underline Science Inc., 2020 BASE Show details 7 On the Sparsity of Neural Machine Translation Models ... Wang, Yong; Wang, Longyue; Li, Victor O. K.. - : arXiv, 2020 BASE Show details 8 Assessing the Bilingual Knowledge Learned by Neural Machine Translation Models ... He, Shilin; Wang, Xing; Shi, Shuming. - : arXiv, 2020 BASE Show details 9 Understanding and Improving Lexical Choice in Non-Autoregressive Translation ... Ding, Liang; Wang, Longyue; Liu, Xuebo. - : arXiv, 2020 BASE Show details 10 Information Aggregation for Multi-Head Attention with Routing-by-Agreement ... Li, Jian; Yang, Baosong; Dou, Zi-Yi. - : arXiv, 2019 BASE Show details 11 Neuron Interaction Based Representation Composition for Neural Machine Translation ... Li, Jian; Wang, Xing; Yang, Baosong. - : arXiv, 2019 BASE Show details 12 Multi-Granularity Self-Attention for Neural Machine Translation ... Hao, Jie; Wang, Xing; Shi, Shuming. - : arXiv, 2019 BASE Show details 13 Towards Understanding Neural Machine Translation with Word Importance ... He, Shilin; Tu, Zhaopeng; Wang, Xing. - : arXiv, 2019 BASE Show details 14 Towards Better Modeling Hierarchical Structure for Self-Attention with Ordered Neurons ... Hao, Jie; Wang, Xing; Shi, Shuming. - : arXiv, 2019 BASE Show details 15 Translating pro-drop languages with reconstruction models Tu, Zhaopeng; Shi, Shuming; Graham, Yvette... In: Wang, Longyue orcid:0000-0002-9062-6183 , Tu, Zhaopeng, Shi, Shuming, Zhang, Tong, Graham, Yvette and Liu, Qun orcid:0000-0002-7000-1792 (2018) Translating pro-drop languages with reconstruction models. In: Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), 2–7 Feb 2018, New Orleans, LA, USA. ISBN 978-1-57735-800-8 (2018) BASE Show details 16 Translating pro-drop languages with reconstruction models Shi, Shuming; Tu, Zhaopeng; Wang, Longyue... In: Wang, Longyue orcid:0000-0002-9062-6183 , Tu, Zhaopeng, Shi, Shuming, Zhang, Tong, Graham, Yvette and Liu, Qun orcid:0000-0002-7000-1792 (2018) Translating pro-drop languages with reconstruction models. In: 32nd AAAI Conference on Artificial Intelligence (AAAI 2018), 2 - 7 Feb 2018, New Orleans, LA, USA. ISBN 978-1-57735-800-8 (2018) BASE Show details 17 Translating Pro-Drop Languages with Reconstruction Models ... Wang, Longyue; Tu, Zhaopeng; Shi, Shuming. - : arXiv, 2018 BASE Show details 18 Exploiting Deep Representations for Neural Machine Translation ... Dou, Zi-Yi; Tu, Zhaopeng; Wang, Xing. - : arXiv, 2018 BASE Show details 19 A novel and robust approach for pro-drop language translation [<Journal>] Wang, Longyue [Verfasser]; Tu, Zhaopeng [Sonstige]; Zhang, Xiaojun [Sonstige]. DNB Subject Category Language Show details 20 Exploiting cross-sentence context for neural machine translation Liu, Qun; Wang, Longyue; Way, Andy... In: Wang, Longyue orcid:0000-0002-9062-6183 , Tu, Zhaopeng, Way, Andy orcid:0000-0001-5736-5930 and Liu, Qun orcid:0000-0002-7000-1792 (2017) Exploiting cross-sentence context for neural machine translation. In: 2017 Conference on Empirical Methods in Natural Language Processing, 7-8 Sept 2017, Copenhagen, Denmark. (2017) BASE Show details Page: 1 2

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