Transfer Learning for Multi-lingual Tasks -- a Survey
Abstract
These days different platforms such as social media provide their clients from different backgrounds and languages the possibility to connect and exchange information. It is not surprising anymore to see comments from different languages in posts published by international celebrities or data providers. In this era, understanding cross languages content and multilingualism in natural language processing (NLP) are hot topics, and multiple efforts have tried to leverage existing technologies in NLP to tackle this challenging research problem. In this survey, we provide a comprehensive overview of the existing literature with a focus on transfer learning techniques in multilingual tasks. We also identify potential opportunities for further research in this domain.
Cite
@article{arxiv.2110.02052,
title = {Transfer Learning for Multi-lingual Tasks -- a Survey},
author = {Amir Reza Jafari and Behnam Heidary and Reza Farahbakhsh and Mostafa Salehi and Mahdi Jalili},
journal= {arXiv preprint arXiv:2110.02052},
year = {2021}
}