@inproceedings{5b87ccd771fe40f295a2895d72880929,
title = "Cross-Lingual Training of Dense Retrievers for Document Retrieval",
abstract = "Dense retrieval has shown great success for passage ranking in English. However, its effectiveness for non-English languages remains unexplored due to limitation in training resources. In this work, we explore different transfer techniques for document ranking from English annotations to non-English languages. Our experiments reveal that zero-shot model-based transfer using mBERT improves search quality. We find that weakly-supervised target language transfer is competitive compared to generation-based target language transfer, which requires translation models.",
author = "Peng Shi and Rui Zhang and He Bai and Jimmy Lin",
note = "Publisher Copyright: {\textcopyright} 2021 Association for Computational Linguistics.; 1st Workshop on Multilingual Representation Learning, MRL 2021 ; Conference date: 11-11-2021",
year = "2021",
doi = "10.18653/v1/2021.mrl-1.24",
language = "English (US)",
series = "MRL 2021 - 1st Workshop on Multilingual Representation Learning, Proceedings of the Conference",
publisher = "Association for Computational Linguistics (ACL)",
pages = "251--253",
editor = "Duygu Ataman and Alexandra Birch and Alexis Conneau and Orhan Firat and Sebastian Ruder and Sahin, {Gozde Gul}",
booktitle = "MRL 2021 - 1st Workshop on Multilingual Representation Learning, Proceedings of the Conference",
}