PERL: Pivot-based Domain Adaptation for Pre-trained Deep Contextualized Embedding Models

16 Jun 2020Eyal Ben-DavidCarmel RabinovitzRoi Reichart

Pivot-based neural representation models have lead to significant progress in domain adaptation for NLP. However, previous works that follow this approach utilize only labeled data from the source domain and unlabeled data from the source and target domains, but neglect to incorporate massive unlabeled corpora that are not necessarily drawn from these domains... (read more)

PDF Abstract

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper