# Cross-Lingual Relevance Transfer for Document Retrieval

arXiv: https://arxiv.org/abs/1911.02989 · HTML: https://mlsanity.com/paper/1911.02989/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Nov 2019.

## Built on by (most cited first, 9 of 9)

- [Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models](https://mlsanity.com/paper/2201.08471/) (2022)
- [Utilizing BERT for Information Retrieval: Survey, Applications, Resources, and Challenges](https://mlsanity.com/paper/2403.00784/) (2024)
- [Neural Approaches to Multilingual Information Retrieval](https://mlsanity.com/paper/2209.01335/) (2022)
- [C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrieval](https://mlsanity.com/paper/2204.11989/) (2022)
- [A Systematic Evaluation of Transfer Learning and Pseudo-labeling with BERT-based Ranking Models](https://mlsanity.com/paper/2103.03335/) (2021)
- [Cross-Lingual Training with Dense Retrieval for Document Retrieval](https://mlsanity.com/paper/2109.01628/) (2021)
- [Multistage BiCross encoder for multilingual access to COVID-19 health information](https://mlsanity.com/paper/2101.03013/) (2021)
- [Distillation for Multilingual Information Retrieval](https://mlsanity.com/paper/2405.00977/) (2024)
- [Cross-language Information Retrieval](https://mlsanity.com/paper/2111.05988/) (2021)

## Abstract (arXiv)

Recent work has shown the surprising ability of multi-lingual BERT to serve as a zero-shot cross-lingual transfer model for a number of language processing tasks. We combine this finding with a similarly-recently proposal on sentence-level relevance modeling for document retrieval to demonstrate the ability of multi-lingual BERT to transfer models of relevance across languages. Experiments on test collections in five different languages from diverse language families (Chinese, Arabic, French, Hindi, and Bengali) show that models trained with English data improve ranking quality, without any special processing, both for (non-English) mono-lingual retrieval as well as cross-lingual retrieval.