Web: http://arxiv.org/abs/2204.02292

Sept. 20, 2022, 1:14 a.m. | Robert Litschko, Ivan Vulić, Goran Glavaš

cs.CL updates on arXiv.org arxiv.org

State-of-the-art neural (re)rankers are notoriously data-hungry which --
given the lack of large-scale training data in languages other than English --
makes them rarely used in multilingual and cross-lingual retrieval settings.
Current approaches therefore commonly transfer rankers trained on English data
to other languages and cross-lingual setups by means of multilingual encoders:
they fine-tune all parameters of pretrained massively multilingual Transformers
(MMTs, e.g., multilingual BERT) on English relevance judgments, and then deploy
them in the target language(s). In this work, …

arxiv cross-lingual retrieval

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