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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 3 Hits 1 – 20 of 52 1 Semantics-Preserved Distortion for Personal Privacy Protection ... Peng, Letian; Li, Zuchao; Zhao, Hai. - : arXiv, 2022 BASE Show details 2 Pre-training Universal Language Representation ... Li, Yian; Zhao, Hai. - : arXiv, 2021 BASE Show details 3 Head-driven Phrase Structure Parsing in O($n^3$) Time Complexity ... Li, Zuchao; Zhou, Junru; Zhao, Hai. - : arXiv, 2021 BASE Show details 4 Multi-tasking Dialogue Comprehension with Discourse Parsing ... He, Yuchen; Zhang, Zhuosheng; Zhao, Hai. - : arXiv, 2021 BASE Show details 5 Structural Pre-training for Dialogue Comprehension ... 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; Zhang, Zhuosheng; Zhao, Hai. - : Underline Science Inc., 2021 BASE Show details 6 Smoothing Dialogue States for Open Conversational Machine Reading ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ouyang, Siru; Zhang, Zhuosheng. - : Underline Science Inc., 2021 BASE Show details 7 Dialogue Graph Modeling for Conversational Machine Reading ... 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; Ouyang, Siru; Zhang, Zhuosheng. - : Underline Science Inc., 2021 BASE Show details 8 Dialogue-oriented Pre-training ... 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; Xu, Yi; Zhao, Hai. - : Underline Science Inc., 2021 BASE Show details 9 Pre-training Universal Language Representation ... 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; Li, Yian; Zhao, Hai. - : Underline Science Inc., 2021 BASE Show details 10 Unsupervised Neural Machine Translation with Universal Grammar ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Li, Zuchao; Sumita, Eiichiro. - : Underline Science Inc., 2021 BASE Show details 11 Seeking Common but Distinguishing Difference, A Joint Aspect-based Sentiment Analysis Model ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Jiang, Shu; Jing, Hongjiang. - : Underline Science Inc., 2021 BASE Show details 12 Enhancing Language Generation with Effective Checkpoints of Pre-trained Language Model ... 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; Park, Jeonghyeok; Zhao, Hai. - : Underline Science Inc., 2021 BASE Show details 13 Syntax Role for Neural Semantic Role Labeling ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Cai, Jiaxun; He, Shexia. - : Underline Science Inc., 2021 BASE Show details 14 Tracing Origins: Coreference-aware Machine Reading Comprehension ... Huang, Baorong; Zhang, Zhuosheng; Zhao, Hai. - : arXiv, 2021 BASE Show details 15 Syntax-aware Data Augmentation for Neural Machine Translation ... Duan, Sufeng; Zhao, Hai; Zhang, Dongdong. - : arXiv, 2020 BASE Show details 16 Cross-lingual Supervision Improves Unsupervised Neural Machine Translation ... Wang, Mingxuan; Bai, Hongxiao; Zhao, Hai; Li, Lei. - : arXiv, 2020 Abstract: Neural machine translation~(NMT) is ineffective for zero-resource languages. Recent works exploring the possibility of unsupervised neural machine translation (UNMT) with only monolingual data can achieve promising results. However, there are still big gaps between UNMT and NMT with parallel supervision. In this work, we introduce a multilingual unsupervised NMT (\method) framework to leverage weakly supervised signals from high-resource language pairs to zero-resource translation directions. More specifically, for unsupervised language pairs \texttt{En-De}, we can make full use of the information from parallel dataset \texttt{En-Fr} to jointly train the unsupervised translation directions all in one model. \method is based on multilingual models which require no changes to the standard unsupervised NMT. Empirical results demonstrate that \method significantly improves the translation quality by more than 3 BLEU score on six benchmark unsupervised translation directions. ... : NAACL Industry Track ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2004.03137 https://arxiv.org/abs/2004.03137 BASE Hide details 17 Syntax Role for Neural Semantic Role Labeling ... Li, Zuchao; Zhao, Hai; He, Shexia. - : arXiv, 2020 BASE Show details 18 BURT: BERT-inspired Universal Representation from Learning Meaningful Segment ... Li, Yian; Zhao, Hai. - : arXiv, 2020 BASE Show details 19 Learning Universal Representations from Word to Sentence ... Li, Yian; Zhao, Hai. - : arXiv, 2020 BASE Show details 20 BURT: BERT-inspired Universal Representation from Twin Structure ... Li, Yian; Zhao, Hai. - : arXiv, 2020 BASE Show details Page: 1 2 3

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