Papers with cross-lingual NLP tasks

3 papers
The Secret is in the Spectra: Predicting Cross-lingual Task Performance with Spectral Similarity Measures (2020.emnlp-main)

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Challenge: Existing studies have suggested that bilingual lexicon induction is influenced by the (dis)similarity of the languages at hand.
Approach: They propose to measure the isomorphism of monolingual embedding spaces based on their spectra and introduce isometric measures to measure their similarity.
Outcome: The proposed measures outperform standard isomorphism measures while being more tractable and easier to interpret.
Unsupervised Joint Training of Bilingual Word Embeddings (P19-1)

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Challenge: Existing methods for unsupervised bilingual word embeddings are limited by the dissimilarity between the word embedded spaces.
Approach: They propose a method that trains unsupervised bilingual word embeddings jointly on parallel data generated through unsupervised machine translation.
Outcome: The proposed method outperforms unsupervised mapped bilingual word embeddings in cross-lingual NLP tasks.
Cross-Lingual Ability of Multilingual Masked Language Models: A Study of Language Structure (2022.acl-long)

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Challenge: Multilingual pre-trained language models have shown impressive cross-lingual ability.
Approach: They argue that cross-language ability comes from commonality between languages . they create an artificial language by modifying property in source language .
Outcome: The proposed model can be implemented in multilingual and low-resource language scenarios without cross-lingual supervision or aligned data.

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