A large body of recent work highlights the fallacies of zero-shot cross-lingual transfer (ZS-
XLT) with large multilingual language models. Namely, their performance varies …

Zero-shot cross-lingual transfer is when a multilingual model is trained to perform a task in
one language and then is applied to another language. Although the zero-shot cross-lingual …

Multilingual language models have pushed state-of-the-art in cross-lingual NLP transfer.
The majority of zero-shot cross-lingual transfer, however, use one and the same massively …

Recent model pruning methods have demonstrated the ability to remove redundant
parameters without sacrificing model performance. Common methods remove redundant …

The rapid development and real-world adoption of natural language processing models in
recent years underscores the imperative to develop such models in different languages. This …

Incorporating language-specific (LS) modules is a proven method to boost performance in
multilingual machine translation. This approach bears similarity to Mixture-of-Experts (MoE) …

Low-resource languages continue to present challenges for current NLP methods, and
multilingual NLP is gaining attention in the research community. One of the main issues is …

Advancements in machine learning have revolutionized natural language processing,
enabling the development of models that can understand and generate multiple languages …