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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 – 13 of 13 1 SMDT: Selective Memory-Augmented Neural Document Translation ... Zhang, Xu; Yang, Jian; Huang, Haoyang. - : arXiv, 2022 BASE Show details 2 DeepNet: Scaling Transformers to 1,000 Layers ... Wang, Hongyu; Ma, Shuming; Dong, Li. - : arXiv, 2022 BASE Show details 3 Zero-shot Cross-lingual Transfer of Prompt-based Tuning with a Unified Multilingual Prompt ... Huang, Lianzhe; Ma, Shuming; Zhang, Dongdong. - : arXiv, 2022 BASE Show details 4 Towards Making the Most of Multilingual Pretraining for Zero-Shot Neural Machine Translation ... Chen, Guanhua; Ma, Shuming; Chen, Yun. - : arXiv, 2021 BASE Show details 5 Zero-shot Cross-lingual Transfer of Neural Machine Translation with Multilingual Pretrained Encoders ... Chen, Guanhua; Ma, Shuming; Chen, Yun. - : arXiv, 2021 BASE Show details 6 Multilingual Machine Translation Systems from Microsoft for WMT21 Shared Task ... Yang, Jian; Ma, Shuming; Huang, Haoyang; Zhang, Dongdong; Dong, Li; Huang, Shaohan; Muzio, Alexandre; Singhal, Saksham; Awadalla, Hany Hassan; Song, Xia; Wei, Furu. - : arXiv, 2021 Abstract: This report describes Microsoft's machine translation systems for the WMT21 shared task on large-scale multilingual machine translation. We participated in all three evaluation tracks including Large Track and two Small Tracks where the former one is unconstrained and the latter two are fully constrained. Our model submissions to the shared task were initialized with DeltaLM\footnote{\url{https://aka.ms/deltalm}}, a generic pre-trained multilingual encoder-decoder model, and fine-tuned correspondingly with the vast collected parallel data and allowed data sources according to track settings, together with applying progressive learning and iterative back-translation approaches to further improve the performance. Our final submissions ranked first on three tracks in terms of the automatic evaluation metric. ... : WMT21 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2111.02086 https://dx.doi.org/10.48550/arxiv.2111.02086 BASE Hide details 7 DeltaLM: Encoder-Decoder Pre-training for Language Generation and Translation by Augmenting Pretrained Multilingual Encoders ... Ma, Shuming; Dong, Li; Huang, Shaohan. - : arXiv, 2021 BASE Show details 8 How Does Distilled Data Complexity Impact the Quality and Confidence of Non-Autoregressive Machine Translation? ... Xu, Weijia; Ma, Shuming; Zhang, Dongdong. - : arXiv, 2021 BASE Show details 9 Syntax-aware Data Augmentation for Neural Machine Translation ... Duan, Sufeng; Zhao, Hai; Zhang, Dongdong. - : arXiv, 2020 BASE Show details 10 M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training ... Ni, Minheng; Huang, Haoyang; Su, Lin. - : arXiv, 2020 BASE Show details 11 XLM-T: Scaling up Multilingual Machine Translation with Pretrained Cross-lingual Transformer Encoders ... Ma, Shuming; Yang, Jian; Huang, Haoyang. - : arXiv, 2020 BASE Show details 12 A Novel Task-Oriented Text Corpus in Silent Speech Recognition and its Natural Language Generation Construction Method ... Cao, Dong; Zhang, Dongdong; Chen, HaiBo. - : arXiv, 2019 BASE Show details 13 Learning Unsupervised Word Mapping by Maximizing Mean Discrepancy ... Yang, Pengcheng; Luo, Fuli; Wu, Shuangzhi. - : arXiv, 2018 BASE Show details

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