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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 – 4 of 4 1 Universal Dependencies 1.4 Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2016 BASE Show details 2 Universal Dependencies 1.3 Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2016 BASE Show details 3 Many Languages, One Parser ... Ammar, Waleed; Mulcaire, George; Ballesteros, Miguel. - : arXiv, 2016 BASE Show details 4 What Do Recurrent Neural Network Grammars Learn About Syntax? ... Kuncoro, Adhiguna; Ballesteros, Miguel; Kong, Lingpeng; Dyer, Chris; Neubig, Graham; Smith, Noah A.. - : arXiv, 2016 Abstract: Recurrent neural network grammars (RNNG) are a recently proposed probabilistic generative modeling family for natural language. They show state-of-the-art language modeling and parsing performance. We investigate what information they learn, from a linguistic perspective, through various ablations to the model and the data, and by augmenting the model with an attention mechanism (GA-RNNG) to enable closer inspection. We find that explicit modeling of composition is crucial for achieving the best performance. Through the attention mechanism, we find that headedness plays a central role in phrasal representation (with the model's latent attention largely agreeing with predictions made by hand-crafted head rules, albeit with some important differences). By training grammars without nonterminal labels, we find that phrasal representations depend minimally on nonterminals, providing support for the endocentricity hypothesis. ... : 10 pages. To appear in EACL 2017, Valencia, Spain ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1611.05774 https://dx.doi.org/10.48550/arxiv.1611.05774 BASE Hide details

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