Data-Efficient Cross-Lingual Transfer with Language-Specific Subnetworks

• URL: http://arxiv.org/abs/2211.00106v1
• Date: Mon, 31 Oct 2022 19:23:33 GMT
• Title: Data-Efficient Cross-Lingual Transfer with Language-Specific Subnetworks
• Authors: Rochelle Choenni, Dan Garrette, Ekaterina Shutova
• Abstract summary: Large multilingual language models typically share their parameters across all languages, which enables cross-lingual task transfer. We propose novel methods for using language-specificworks, which control cross-lingual parameter sharing. We combine our methods with meta-learning, an established, but complementary, technique for improving cross-lingual transfer.
• Score: 16.8212280804151
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Large multilingual language models typically share their parameters across all languages, which enables cross-lingual task transfer, but learning can also be hindered when training updates from different languages are in conflict. In this paper, we propose novel methods for using language-specific subnetworks, which control cross-lingual parameter sharing, to reduce conflicts and increase positive transfer during fine-tuning. We introduce dynamic subnetworks, which are jointly updated with the model, and we combine our methods with meta-learning, an established, but complementary, technique for improving cross-lingual transfer. Finally, we provide extensive analyses of how each of our methods affects the models.

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