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Exploring cross-lingual word embeddings for the inference of bilingual dictionaries
2019
International Conference on Language, Data, and Knowledge
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All four methods make use of cross-lingual word embeddings trained on monolingual corpora, and then mapped into a shared vector space. ...
We describe four systems to generate automatically bilingual dictionaries based on existing ones: three transitive systems differing only in the pivot language used, and a system based on a different approach ...
Algorithm With a view to exploring solely the performance of cross-lingual word embeddings in this task, it must be noted that our approach only uses the first and last columns of the input data (the source ...
dblp:conf/ldk/GarciaGA19
fatcat:rtxyxfhjsfhjtdxdrmxc5l5ja4
On the Robustness of Unsupervised and Semi-supervised Cross-lingual Word Embedding Learning
[article]
2020
arXiv
pre-print
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Cross-lingual word embeddings are vector representations of words in different languages where words with similar meaning are represented by similar vectors, regardless of the language. ...
Our conclusions put in doubt the view that high-quality cross-lingual embeddings can always be learned without much supervision. ...
Evaluation We use two standard tasks for evaluating cross-lingual word embeddings: bilingual dictionary induction (Section 5.1) and cross-lingual word similarity (Section 5.2). ...
arXiv:1908.07742v4
fatcat:jbbd35pomndfjjeebzugbsyy24
Graph Exploration and Cross-lingual Word Embeddings for Translation Inference Across Dictionaries
2020
Zenodo
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To that end, we essayed two different types of techniques: based on graph exploration on the one hand and, on the other hand, based on cross-lingual word embeddings. ...
The aim of the task is to automatically generate new bilingual dictionaries from existing ones. ...
A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings. ...
doi:10.5281/zenodo.3898278
fatcat:4asperaxhzdflnlksnu6ybu3zy
Baselines and test data for cross-lingual inference
[article]
2018
arXiv
pre-print
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Our systems are based on cross-lingual word embeddings and machine translation. ...
The recent years have seen a revival of interest in textual entailment, sparked by i) the emergence of powerful deep neural network learners for natural language processing and ii) the timely development ...
In experiments with three types of transfer systems, we record viable scores, while at the same time exploring the scalability of cross-lingual inference for low-resource languages. ...
arXiv:1704.05347v2
fatcat:pbzvb2x6sbaupairgfoavj6zg4
Meemi: A Simple Method for Post-processing and Integrating Cross-lingual Word Embeddings
[article]
2020
arXiv
pre-print
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tasks such as cross-lingual hypernym discovery and cross-lingual natural language inference. ...
While monolingual word embeddings encode information about words in the context of a particular language, cross-lingual embeddings define a multilingual space where word embeddings from two or more languages ...
Acknowledgments Yerai Doval has been supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO) through the ANSWER-ASAP project (TIN2017-85160-C2-2-R); by the Spanish State Secretariat ...
arXiv:1910.07221v4
fatcat:ezeepywtkfdqbalfdpa6vpqqdy
Learning to Represent Bilingual Dictionaries
2019
Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)
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The proposed model is trained to map the lexical definitions to the cross-lingual target words, for which we explore with different sentence encoding techniques. ...
Bilingual word embeddings have been widely used to capture the correspondence of lexical semantics in different human languages. ...
Acknowledgement We thank the anonymous reviewers for their insightful comments. This work was supported in part by National Science Foundation Grant IIS-1760523. ...
doi:10.18653/v1/k19-1015
dblp:conf/conll/ChenTCCSZ19
fatcat:acovrv3wuzbtnnifgysnrkc63q
English–Welsh Cross-Lingual Embeddings
2021
Applied Sciences
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In this paper, we present and evaluate a suite of cross-lingual embeddings for the English–Welsh language pair. ...
We evaluated different combinations of these approaches using two tasks, bilingual dictionary induction, and cross-lingual sentiment analysis. ...
Acknowledgments: The research on which this article is based was funded by the Welsh Government as part of the "Learning English-Welsh bilingual embeddings and applications in text categorisation" project ...
doi:10.3390/app11146541
fatcat:aht2dnh6xje4ldtw5zhdimmkea
LLOD-Driven Bilingual Word Embeddings Rivaling Cross-Lingual Transformers in Quality of Life Concept Detection from French Online Health Communities
[chapter]
2021
Applications and Practices in Ontology Design, Extraction, and Reasoning
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Cross-lingual supervision is provided by LLOD lexical resources to learn bilingual word embeddings that are simultaneously tuned to represent an inventory of HRQoL concepts based on the World Health Organization's ...
We describe the use of Linguistic Linked Open Data (LLOD) to support a cross-lingual transfer framework for concept detection in online health communities. ...
Acknowledgments This work was funded by the Prêt-à-LLOD project within the European Union's Horizon 2020 research and innovation programme under grant agreement no. 825182. ...
doi:10.3233/ssw210037
fatcat:nvmixudmg5gy5naedlaezqlkbi
Scalable Cross-Lingual Transfer of Neural Sentence Embeddings
[article]
2019
arXiv
pre-print
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We develop and investigate several cross-lingual alignment approaches for neural sentence embedding models, such as the supervised inference classifier, InferSent, and sequential encoder-decoder models ...
Our results support representation transfer as a scalable approach for modular cross-lingual alignment of neural sentence embeddings, where we observe better performance compared to joint models in intrinsic ...
Conclusions We explored different approaches for cross-lingual alignment of top-down sentence embedding models: joint modeling, representation transfer, and sentence mapping. ...
arXiv:1904.05542v1
fatcat:cvmxdq7kvzbhphsanx5rlq6rbi
Scalable Cross-Lingual Transfer of Neural Sentence Embeddings
2019
Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*
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Our results support representation transfer as a scalable approach for modular cross-lingual alignment of neural sentence embeddings, where we observe better performance compared to joint models in intrinsic ...
We develop and investigate several crosslingual alignment approaches for neural sentence embedding models, such as the supervised inference classifier, InferSent, and sequential encoder-decoder models. ...
Conclusions We explored different approaches for cross-lingual alignment of top-down sentence embedding models: joint modeling, representation transfer, and sentence mapping. ...
doi:10.18653/v1/s19-1006
dblp:conf/starsem/AldarmakiD19
fatcat:oxgda73bpfcsphfh5vdpuhkeiy
LLOD-driven Bilingual Word Embeddings Rivaling Cross-lingual Transformers in Quality of Life Concept Detection from French Online Health Communities
2021
Zenodo
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Cross-lingual supervision is provided by LLOD lexical resources to learn bilingual word embeddings that are simultaneously tuned to represent an inventory of HRQoL concepts based on the World Health Organization's ...
We describe the use of Linguistic Linked Open Data (LLOD) to support a cross-lingual transfer framework for concept detection in online health communities. ...
Acknowledgments This work was funded by the Prêt-à-LLOD project within the European Union's Horizon 2020 research and innovation programme under grant agreement no. 825182. ...
doi:10.5281/zenodo.5011771
fatcat:3t6upx3orjcxzirw5vqsdwp3wu
Context-Aware Cross-Lingual Mapping
[article]
2019
arXiv
pre-print
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Cross-lingual word vectors are typically obtained by fitting an orthogonal matrix that maps the entries of a bilingual dictionary from a source to a target vector space. ...
We also implement cross-lingual mapping of deep contextualized word embeddings using parallel sentences with word alignments. ...
One of the most common and effective approaches for obtaining bilingual word embeddings is by fitting a linear transformation matrix on the entries of a bilingual seed dictionary (Mikolov et al., 2013 ...
arXiv:1903.03243v2
fatcat:bgy3m2lhurdrjkhcojmgiu5pjm
Context-Aware Cross-Lingual Mapping
2019
Proceedings of the 2019 Conference of the North
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Cross-lingual word vectors are typically obtained by fitting an orthogonal matrix that maps the entries of a bilingual dictionary from a source to a target vector space. ...
We also implement cross-lingual mapping of deep contextualized word embeddings using parallel sentences with word alignments. ...
One of the most common and effective approaches for obtaining bilingual word embeddings is by fitting a linear transformation matrix on the entries of a bilingual seed dictionary (Mikolov et al., 2013 ...
doi:10.18653/v1/n19-1391
dblp:conf/naacl/AldarmakiD19
fatcat:wzw7ssx3over7h3uk6heh6siwu
A Survey of Cross-lingual Word Embedding Models
2019
The Journal of Artificial Intelligence Research
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We also discuss the different ways cross-lingual word embeddings are evaluated, as well as future challenges and research horizons. ...
Cross-lingual representations of words enable us to reason about word meaning in multilingual contexts and are a key facilitator of cross-lingual transfer when developing natural language processing models ...
Acknowledgements We thank the anonymous reviewers and the editors for their valuable and comprehensive feedback. ...
doi:10.1613/jair.1.11640
fatcat:vwlgtzzmhfdlnlyaokx2whxgva
Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric Approach
[article]
2018
arXiv
pre-print
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We show that our approach outperforms previous approaches on the bilingual lexicon induction and cross-lingual word similarity tasks. ...
We propose a novel geometric approach for learning bilingual mappings given monolingual embeddings and a bilingual dictionary. ...
posed latent space representation of multiple languages by sharing annotated resources across languages. ...
arXiv:1808.08773v3
fatcat:tkic4ej7drbc3glenbnop6wkja
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