2021
EMNLP
EMNLP 2021
Cross-Lingual Training of Dense Retrievers for Document Retrieval
Abstract
AbstractDense 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.
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Interdisciplinary Bridge
- Artificial Intelligence and Computer Science and Natural Language Processing
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Hot Topic Early Bird
- cross-lingual retrieval
Topics
Artificial Intelligence > Learning Paradigms > Transfer Learning
Machine Learning > Application Areas > Domain Adaptation
Natural Language Processing > Applications > Information Retrieval
Natural Language Processing > Resources & Methods > Multilingual NLP
Computer Science > Applications > Information Retrieval
Machine Learning > Learning Types > Transfer Learning
Artificial Intelligence > Core AI > Information Retrieval
Deep Learning > Learning Types > Retrieval-Augmented Generation