2018 WhenandWhyArePreTrainedWordEmbe

• (Qi et al., 2018) ⇒ Ye Qi, Devendra Singh Sachan, Matthieu Felix, Sarguna Padmanabhan, and Graham Neubig. (2018). “When and Why Are Pre-Trained Word Embeddings Useful for Neural Machine Translation?.” In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2018) Volume 2 (Short Papers). DOI:10.18653/v1/N18-2084 .

Subject Headings: Word Embeddings; Neural Machine Translation.

Notes

• Computing Resource(s):
  • Software: https://www.aclweb.org/anthology/attachments/N18-2084.Software.tgz
• Other Link(s):
  • ACL Anthology: https://www.aclweb.org/anthology/N18-2084/
  • ArXiv: https://arxiv.org/abs/1804.06323
  • DBLP: https://dblp.org/rec/html/conf/naacl/QiSFPN18

Cited By

• Google Scholar: ~ 72 Citations, Retrieved:2020-06-07.
• Semantic Scholar: ~ 89 Citations, Retrieved:2020-06-07.
• MS Academic: ~ 63 Citations, Retrieved:2020-06-07.

Quotes

Abstract

The performance of Neural Machine Translation (NMT) systems often suffers in low-resource scenarios where sufficiently large-scale parallel corpora cannot be obtained. Pre-trained word embeddings have proven to be invaluable for improving performance in natural language analysis tasks, which often suffer from paucity of data. However, their utility for NMT has not been extensively explored. In this work, we perform five sets of experiments that analyze when we can expect pre-trained word embeddings to help in NMT tasks. We show that such embeddings can be surprisingly effective in some cases – providing gains of up to 20 BLEU points in the most favorable setting.

BibTeX

@inproceedings{2018_WhenandWhyArePreTrainedWordEmbe,
  author    = {Ye Qi and
               Devendra Singh Sachan and
               Matthieu Felix and
               Sarguna Padmanabhan and
               Graham Neubig},
  editor    = {Marilyn A. Walker and
               Heng Ji and
               Amanda Stent},
  title     = {When and Why Are Pre-Trained Word Embeddings Useful for Neural Machine
               Translation?},
  booktitle = {Proceedings of the 2018 Conference of the North American Chapter of
               the Association for Computational Linguistics: Human Language Technologies,
               (NAACL-HLT 2018)  Volume 2 (Short Papers), New Orleans, Louisiana, USA, June 1-6, 2018,},
  pages     = {529--535},
  publisher = {Association for Computational Linguistics},
  year      = {2018},
  url       = {https://doi.org/10.18653/v1/n18-2084},
  doi       = {10.18653/v1/n18-2084},
}

---

	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2018 WhenandWhyArePreTrainedWordEmbe	Graham Neubig Devendra Singh Sachan Ye Qi Matthieu Felix Sarguna Padmanabhan			When and Why Are Pre-Trained Word Embeddings Useful for Neural Machine Translation?						2018