Cross-Lingual Word Embeddings
31 papers with code • 0 benchmarks • 0 datasets
Benchmarks
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Libraries
Use these libraries to find Cross-Lingual Word Embeddings models and implementationsMost implemented papers
A Resource-Free Evaluation Metric for Cross-Lingual Word Embeddings Based on Graph Modularity
Cross-lingual word embeddings encode the meaning of words from different languages into a shared low-dimensional space.
Interactive Refinement of Cross-Lingual Word Embeddings
forest-snow/clime-ui
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EMNLP 2020
Cross-lingual word embeddings transfer knowledge between languages: models trained on high-resource languages can predict in low-resource languages.
Should All Cross-Lingual Embeddings Speak English?
Most of recent work in cross-lingual word embeddings is severely Anglocentric.
Machine Translation with Cross-lingual Word Embeddings
Learning word embeddings using distributional information is a task that has been studied by many researchers, and a lot of studies are reported in the literature.
Two-Level Transformer and Auxiliary Coherence Modeling for Improved Text Segmentation
EducationalTestingService/CATS
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Breaking down the structure of long texts into semantically coherent segments makes the texts more readable and supports downstream applications like summarization and retrieval.
Refinement of Unsupervised Cross-Lingual Word Embeddings
In this paper, we propose a self-supervised method to refine the alignment of unsupervised bilingual word embeddings.
MultiSeg: Parallel Data and Subword Information for Learning Bilingual Embeddings in Low Resource Scenarios
Our results show that our method that leverages subword information outperforms the model without subword information, both in intrinsic and extrinsic evaluations of the learned embeddings.
Cross-Lingual Word Embeddings for Turkic Languages
Our experiments confirm that the obtained bilingual dictionaries outperform previously-available ones, and that word embeddings from a low-resource language can benefit from resource-rich closely-related languages when they are aligned together.
Learning Contextualised Cross-lingual Word Embeddings and Alignments for Extremely Low-Resource Languages Using Parallel Corpora
twadada/multilingual-nlm
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EMNLP (MRL) 2021
We propose a new approach for learning contextualised cross-lingual word embeddings based on a small parallel corpus (e. g. a few hundred sentence pairs).
Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval
Therefore, in this work we present a systematic empirical study focused on the suitability of the state-of-the-art multilingual encoders for cross-lingual document and sentence retrieval tasks across a large number of language pairs.
