Papers with cross-domain LM contrast

1 papers
Cross-Domain NER using Cross-Domain Language Modeling (P19-1)

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Challenge: Existing methods for named entity recognition (NER) use labeled data for both source and target domains.
Approach: They propose to use language modeling as a bridge between NER domains to perform cross-domain and cross-task knowledge transfer.
Outcome: The proposed method extracts domain differences from cross-domain LM contrast, allowing unsupervised domain adaptation while giving state-of-the-art results among supervised domain adapters.

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