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1
Substructure Substitution: Structured Data Augmentation for NLP ...
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Bilingual Lexicon Induction via Unsupervised Bitext Construction and Word Alignment ...
Abstract: Bilingual lexicons map words in one language to their translations in another, and are typically induced by learning linear projections to align monolingual word embedding spaces. In this paper, we show it is possible to produce much higher quality lexicons with methods that combine (1) unsupervised bitext mining and (2) unsupervised word alignment. Directly applying a pipeline that uses recent algorithms for both subproblems significantly improves induced lexicon quality and further gains are possible by learning to filter the resulting lexical entries, with both unsupervised and semi-supervised schemes. Our final model outperforms the state of the art on the BUCC 2020 shared task by 14 $F_1$ points averaged over 12 language pairs, while also providing a more interpretable approach that allows for rich reasoning of word meaning in context. Further analysis of our output and the standard reference lexicons suggests they are of comparable quality, and new benchmarks may be needed to measure further progress ... : ACL-IJCNLP 2021 camera-ready version, with full supplementary material ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2101.00148
https://arxiv.org/abs/2101.00148
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3
Bilingual Lexicon Induction via Unsupervised Bitext Construction and Word Alignment ...
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4
Deep Clustering of Text Representations for Supervision-free Probing of Syntax ...
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5
Understanding and Improving Multi-Sense Word Embeddings via Extended Robust Principal Component Analysis ...
Shi, Haoyue; Sun, Yuqi; Hu, Junfeng. - : arXiv, 2018
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6
Learning Visually-Grounded Semantics from Contrastive Adversarial Samples ...
Shi, Haoyue; Mao, Jiayuan; Xiao, Tete. - : arXiv, 2018
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7
Real Multi-Sense or Pseudo Multi-Sense: An Approach to Improve Word Representation ...
Shi, Haoyue; Li, Caihua; Hu, Junfeng. - : arXiv, 2017
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