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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 – 5 of 5 1 G-Transformer for Document-Level 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; ., Boxing; Bao, Guangsheng. - : Underline Science Inc., 2021 BASE Show details 2 End-to-End Chinese Parsing Exploiting Lexicons ... Zhang, Yuan; Teng, Zhiyang; Zhang, Yue. - : arXiv, 2020 BASE Show details 3 Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning Guo, Zhijiang; Zhang, Yan; Teng, Zhiyang; Lu, Wei In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 297-312 (2019) (2019) Abstract: We focus on graph-to-sequence learning, which can be framed as transducing graph structures to sequences for text generation. To capture structural information associated with graphs, we investigate the problem of encoding graphs using graph convolutional networks (GCNs). Unlike various existing approaches where shallow architectures were used for capturing local structural information only, we introduce a dense connection strategy, proposing a novel Densely Connected Graph Convolutional Network (DCGCN). Such a deep architecture is able to integrate both local and non-local features to learn a better structural representation of a graph. Our model outperforms the state-of-the-art neural models significantly on AMR-to-text generation and syntax-based neural machine translation. Keyword: Computational linguistics. Natural language processing; P98-98.5 URL: https://doi.org/10.1162/tacl_a_00269 https://doaj.org/article/f2b7fafd486c43a690860431d00bc558 BASE Hide details 4 Combining Discrete and Neural Features for Sequence Labeling ... Yang, Jie; Teng, Zhiyang; Zhang, Meishan. - : arXiv, 2017 BASE Show details 5 Bidirectional Tree-Structured LSTM with Head Lexicalization ... Teng, Zhiyang; Zhang, Yue. - : arXiv, 2016 BASE Show details

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