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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 Generative Data Augmentation for Commonsense Reasoning ... Yang, Yiben; Malaviya, Chaitanya; Fernandez, Jared. - : arXiv, 2020 BASE Show details 2 The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection ... McCarthy, Arya D.; Vylomova, Ekaterina; Wu, Shijie. - : arXiv, 2019 BASE Show details 3 Neural Factor Graph Models for Cross-lingual Morphological Tagging ... Malaviya, Chaitanya; Gormley, Matthew R.; Neubig, Graham. - : arXiv, 2018 Abstract: Morphological analysis involves predicting the syntactic traits of a word (e.g. {POS: Noun, Case: Acc, Gender: Fem}). Previous work in morphological tagging improves performance for low-resource languages (LRLs) through cross-lingual training with a high-resource language (HRL) from the same family, but is limited by the strict, often false, assumption that tag sets exactly overlap between the HRL and LRL. In this paper we propose a method for cross-lingual morphological tagging that aims to improve information sharing between languages by relaxing this assumption. The proposed model uses factorial conditional random fields with neural network potentials, making it possible to (1) utilize the expressive power of neural network representations to smooth over superficial differences in the surface forms, (2) model pairwise and transitive relationships between tags, and (3) accurately generate tag sets that are unseen or rare in the training data. Experiments on four languages from the Universal Dependencies ... : Proceedings of ACL 2018 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1805.04570 https://arxiv.org/abs/1805.04570 BASE Hide details 4 Learning Language Representations for Typology Prediction ... Malaviya, Chaitanya; Neubig, Graham; Littell, Patrick. - : arXiv, 2017 BASE Show details

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