@InProceedings{garneau-leboeuf-lamontagne:2018:BlackboxNLP,
  author    = {Garneau, Nicolas  and  Leboeuf, Jean-Samuel  and  Lamontagne, Luc},
  title     = {Predicting and interpreting embeddings for out of vocabulary words in downstream tasks},
  booktitle = {Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP},
  month     = {November},
  year      = {2018},
  address   = {Brussels, Belgium},
  publisher = {Association for Computational Linguistics},
  pages     = {331--333},
  abstract  = {We propose a novel way to handle out of vocabulary (OOV) words in downstream natural language processing (NLP) tasks. We implement a network that predicts useful embeddings for OOV words based on their morphology and on the context in which they appear. Our model also incorporates an attention mechanism indicating the focus allocated to the left context words, the right context words or the word’s characters, hence making the prediction more interpretable. The model is a},
  url       = {http://www.aclweb.org/anthology/W18-5439}
}