Papers with single source domain adaptation

1 papers
Biomedical Relation Classification by single and multiple source domain adaptation (D19-62)

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Challenge: Existing supervised systems are highly data-driven and require a lot of effort to label data for a new domain.
Approach: They propose to transfer knowledge from one or more related source domains to another domain to improve relation classification.
Outcome: The proposed model outperforms neural-network based models on biomedical datasets and with contextualized embeddings on 3 biomedically-relevant datasets.

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