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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 – 12 of 12 1 Orthographic facilitation in oral vocabulary learning: effects of language backgrounds and orthographic type [<Journal>] Zhang, Jie [Verfasser]; Chen, Yu [Verfasser]; Liu, Yang [Verfasser]. DNB Subject Category Language Show details 2 Chinese computational linguistics : 18th China National Conference, CCL 2019, Kunming, China, October 18-20, 2019 : proceedings Liu, Zhiyuan (Herausgeber); Jiang, Heng (Herausgeber); Liu, Yang (Herausgeber). - Cham, Switzerland : Springer, 2019 BLLDB UB Frankfurt Linguistik Show details 3 Measurement of $W^{\pm}$-boson and $Z$-boson production cross-sections in $pp$ collisions at $\sqrt{s}=2.76$ TeV with the ATLAS detector Aad, Georges; Abbott, Brad; Abbott, Dale Charles. - 2019 BASE Show details 4 Shared-Private Bilingual Word Embeddings for Neural Machine Translation ... Liu, Xuebo; Wong, Derek F.; Liu, Yang; Chao, Lidia S.; Xiao, Tong; Zhu, Jingbo. - : arXiv, 2019 Abstract: Word embedding is central to neural machine translation (NMT), which has attracted intensive research interest in recent years. In NMT, the source embedding plays the role of the entrance while the target embedding acts as the terminal. These layers occupy most of the model parameters for representation learning. Furthermore, they indirectly interface via a soft-attention mechanism, which makes them comparatively isolated. In this paper, we propose shared-private bilingual word embeddings, which give a closer relationship between the source and target embeddings, and which also reduce the number of model parameters. For similar source and target words, their embeddings tend to share a part of the features and they cooperatively learn these common representation units. Experiments on 5 language pairs belonging to 6 different language families and written in 5 different alphabets demonstrate that the proposed model provides a significant performance boost over the strong baselines with dramatically fewer model ... : Accepted to ACL 2019 ... Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1906.03100 https://dx.doi.org/10.48550/arxiv.1906.03100 BASE Hide details 5 Improving Back-Translation with Uncertainty-based Confidence Estimation ... Wang, Shuo; Liu, Yang; Wang, Chao. - : arXiv, 2019 BASE Show details 6 Additional file 1: of HIV prevalence in suspected Ebola cases during the 2014â 2016 Ebola epidemic in Sierra Leone ... Liu, William; Hu, Hai-Yang; Qiu-Dong Su. - : figshare, 2019 BASE Show details 7 Additional file 1: of HIV prevalence in suspected Ebola cases during the 2014â 2016 Ebola epidemic in Sierra Leone ... Liu, William; Hu, Hai-Yang; Qiu-Dong Su. - : figshare, 2019 BASE Show details 8 An Augmented Transformer Architecture for Natural Language Generation Tasks ... Li, Hailiang; Wang, Adele Y. C.; Liu, Yang. - : arXiv, 2019 BASE Show details 9 Neural Machine Translation with Explicit Phrase Alignment ... Zhang, Jiacheng; Luan, Huanbo; Sun, Maosong. - : arXiv, 2019 BASE Show details 10 Factors affecting bimodal benefit in pediatric Mandarin-speaking Chinese cochlear implant users Liu, Yang-Wenyi; Tao, Duo-Duo; Chen, Bing... In: Ear Hear (2019) BASE Show details 11 Discourse Relations and Signaling Information: Anchoring Discourse Signals in RST-DT Liu, Yang; Zeldes, Amir In: Proceedings of the Society for Computation in Linguistics (2019) BASE Show details 12 Adpositional Supersenses for Mandarin Chinese Zhu, Yilun; Liu, Yang; Peng, Siyao... In: Proceedings of the Society for Computation in Linguistics (2019) BASE Show details

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