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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 Hits 1 – 20 of 28 1 Data-to-text generation with neural planning Puduppully, Ratish Surendran. - : The University of Edinburgh, 2022 BASE Show details 2 Intrinsic Bias Metrics Do Not Correlate with Application Bias ... 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; Goldfarb-Tarrant, Seraphina; Lopez, Adam. - : Underline Science Inc., 2021 BASE Show details 3 Training dynamics of neural language models Saphra, Naomi. - : The University of Edinburgh, 2021 BASE Show details 4 Inflecting when there's no majority: Limitations of encoder-decoder neural networks as cognitive models for German plurals ... McCurdy, Kate; Goldwater, Sharon; Lopez, Adam. - : arXiv, 2020 BASE Show details 5 Understanding and generating language with abstract meaning representation Damonte, Marco. - : The University of Edinburgh, 2020 BASE Show details 6 On understanding character-level models for representing morphology Vania, Clara. - : The University of Edinburgh, 2020 BASE Show details 7 Methods for morphology learning in low(er)-resource scenarios Bergmanis, Toms. - : The University of Edinburgh, 2020 BASE Show details 8 Modelling speaker adaptation in second language learner dialogue Sinclair, Arabella Jane. - : The University of Edinburgh, 2020 BASE Show details 9 Semantic Graph Parsing with Recurrent Neural Network DAG Grammars ... Fancellu, Federico; Gilroy, Sorcha; Lopez, Adam. - : arXiv, 2019 BASE Show details 10 Lifecycle of neural semantic parsing Cheng, Jianpeng. - : The University of Edinburgh, 2019 BASE Show details 11 Fast machine translation on parallel and massively parallel hardware Bogoychev, Nikolay Veselinov. - : The University of Edinburgh, 2019 BASE Show details 12 Learning natural language interfaces with neural models Dong, Li. - : The University of Edinburgh, 2019 BASE Show details 13 Probabilistic graph formalisms for meaning representations Gilroy, Sorcha. - : The University of Edinburgh, 2019 Abstract: In recent years, many datasets have become available that represent natural language semantics as graphs. To use these datasets in natural language processing (NLP), we require probabilistic models of graphs. Finite-state models have been very successful for NLP tasks on strings and trees because they are probabilistic and composable. Are there equivalent models for graphs? In this thesis, we survey several graph formalisms, focusing on whether they are probabilistic and composable, and we contribute several new results. In particular, we study the directed acyclic graph automata languages (DAGAL), the monadic second-order graph languages (MSOGL), and the hyperedge replacement languages (HRL). We prove that DAGAL cannot be made probabilistic, we explain why MSOGL also most likely cannot be made probabilistic, and we review the fact that HRL are not composable. We then review a subfamily of HRL and MSOGL: the regular graph languages (RGL; Courcelle 1991), which have not been widely studied, and particularly have not been studied in an NLP context. Although Courcelle (1991) only sketches a proof, we present a full, more NLP-accessible proof that RGL are a subfamily of MSOGL. We prove that RGL are probabilistic and composable, and we provide a novel Earley-style parsing algorithm for them that runs in time linear in the size of the input graph. We compare RGL to two other new formalisms: the restricted DAG languages (RDL; Bj¨orklund et al. 2016) and the tree-like languages (TLL; Matheja et al. 2015). We show that RGL and RDL are incomparable; TLL and RDL are incomparable; and either RGL are incomparable to TLL, or RGL are contained within TLL. This thesis provides a clearer picture of this field from an NLP perspective, and suggests new theoretical and empirical research directions. Keyword: DAGAL; directed acyclic graph automata languages; graph formalisms; HRL; hyperedge replacement languages; monadic second-order graph languages; MSOGL URL: http://hdl.handle.net/1842/35606 BASE Hide details 14 Low-resource speech translation Bansal, Sameer. - : The University of Edinburgh, 2019 BASE Show details 15 Indicatements that character language models learn English morpho-syntactic units and regularities ... Kementchedjhieva, Yova; Lopez, Adam. - : arXiv, 2018 BASE Show details 16 Neural Networks for Cross-lingual Negation Scope Detection ... Fancellu, Federico; Lopez, Adam; Webber, Bonnie. - : arXiv, 2018 BASE Show details 17 Understanding Learning Dynamics Of Language Models with SVCCA ... Saphra, Naomi; Lopez, Adam. - : arXiv, 2018 BASE Show details 18 Entity-based coherence in statistical machine translation: a modelling and evaluation perspective Wetzel, Dominikus Emanuel. - : The University of Edinburgh, 2018 BASE Show details 19 Computational models for multilingual negation scope detection Fancellu, Federico. - : The University of Edinburgh, 2018 BASE Show details 20 CoNLL 2017 Shared Task System Outputs Zeman, Daniel; Potthast, Martin; Straka, Milan. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2017 BASE Show details Page: 1 2

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