@InProceedings{kann-cotterell-schutze:2017:Long,
  author    = {Kann, Katharina  and  Cotterell, Ryan  and  Sch\"{u}tze, Hinrich},
  title     = {One-Shot Neural Cross-Lingual Transfer for Paradigm Completion},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {1993--2003},
  abstract  = {We present a novel cross-lingual transfer method for paradigm completion, the
	task of mapping a lemma to its inflected forms, using a neural encoder-decoder
	model, the state of the art for the monolingual task. We use labeled data from
	a high-resource language to increase performance on a low-resource language. In
	experiments on 21 language pairs from four different language families, we
	obtain up to 58% higher accuracy than without transfer and show that even
	zero-shot and one-shot learning are possible. We further find that the degree
	of language relatedness strongly influences the ability to transfer
	morphological knowledge.},
  url       = {http://aclweb.org/anthology/P17-1182}
}