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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 Unsupervised Bilingual Lexicon Induction Across Writing Systems ... Riley, Parker; Gildea, Daniel. - : arXiv, 2020 BASE Show details 2 N-ary Relation Extraction using Graph State LSTM ... Song, Linfeng; Zhang, Yue; Wang, Zhiguo. - : arXiv, 2018 BASE Show details 3 Addressing the Data Sparsity Issue in Neural AMR Parsing ... Peng, Xiaochang; Wang, Chuan; Gildea, Daniel. - : arXiv, 2017 BASE Show details 4 Sense Embedding Learning for Word Sense Induction ... Song, Linfeng; Wang, Zhiguo; Mi, Haitao. - : arXiv, 2016 BASE Show details 5 Human languages order information efficiently ... Gildea, Daniel; Jaeger, T. Florian. - : arXiv, 2015 Abstract: Most languages use the relative order between words to encode meaning relations. Languages differ, however, in what orders they use and how these orders are mapped onto different meanings. We test the hypothesis that, despite these differences, human languages might constitute different `solutions' to common pressures of language use. Using Monte Carlo simulations over data from five languages, we find that their word orders are efficient for processing in terms of both dependency length and local lexical probability. This suggests that biases originating in how the brain understands language strongly constrain how human languages change over generations. ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1510.02823 https://arxiv.org/abs/1510.02823 BASE Hide details

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