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Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models
[article]
2022
arXiv
pre-print
The advent of transformer-based models such as BERT has led to the rise of neural ranking models. These models have improved the effectiveness of retrieval systems well beyond that of lexical term matching models such as BM25. While monolingual retrieval tasks have benefited from large-scale training collections such as MS MARCO and advances in neural architectures, cross-language retrieval tasks have fallen behind these advancements. This paper introduces ColBERT-X, a generalization of the
arXiv:2201.08471v1
fatcat:qotjmi4dmner3cqxym6ad3ol3q