@InProceedings{wu-EtAl:2018:NEWS2018,
  author    = {Wu, Jiewen  and  Banchs, Rafael E.  and  D'Haro, Luis Fernando  and  Krishnaswamy, Pavitra  and  Chen, Nancy},
  title     = {Attention-based Semantic Priming for Slot-filling},
  booktitle = {Proceedings of the Seventh Named Entities Workshop},
  month     = {July},
  year      = {2018},
  address   = {Melbourne, Australia},
  publisher = {Association for Computational Linguistics},
  pages     = {22--26},
  abstract  = {The problem of sequence labelling in language understanding would benefit from approaches inspired by semantic priming phenomena. We propose that an attention-based RNN architecture can be used to simulate semantic priming for sequence labelling. Specifically, we employ pre-trained word embeddings to characterize the semantic relationship between utterances and labels. We validate the approach using varying sizes of the ATIS and MEDIA datasets, and show up to 1.4-1.9% improvement in F1 score. The developed framework can enable more explainable and generalizable spoken language understanding systems.},
  url       = {http://www.aclweb.org/anthology/W18-2404}
}