Low-Resource Sequence Labeling via Unsupervised Multilingual Contextualized Representations

EMNLP 2019 Zuyi BaoRui HuangChen LiKenny Q. Zhu

Previous work on cross-lingual sequence labeling tasks either requires parallel data or bridges the two languages through word-byword matching. Such requirements and assumptions are infeasible for most languages, especially for languages with large linguistic distances, e.g., English and Chinese... (read more)

PDF Abstract


No code implementations yet. Submit your code now

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.