@InProceedings{rnning-hardt-sgaard:2018:N18-2,
  author    = {Rønning, Ola  and  Hardt, Daniel  and  Søgaard, Anders},
  title     = {Sluice Resolution without Hand-Crafted Features over Brittle Syntax Trees},
  booktitle = {Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)},
  month     = {June},
  year      = {2018},
  address   = {New Orleans, Louisiana},
  publisher = {Association for Computational Linguistics},
  pages     = {236--241},
  abstract  = {Sluice resolution in English is the problem of finding antecedents of {\em wh}-fronted ellipses. Previous work has relied on hand-crafted features over syntax trees that scale poorly to other languages and domains; in particular, to dialogue, which is one of the most interesting applications of sluice resolution. Syntactic information is arguably important for sluice resolution, but we show that multi-task learning with partial parsing as auxiliary tasks effectively closes the gap and buys us an additional 9\%~error reduction over previous work. Since we are not directly relying on features from partial parsers, our system is more robust to domain shifts, giving a 26\%~error reduction on embedded sluices in dialogue.},
  url       = {http://www.aclweb.org/anthology/N18-2038}
}