@inproceedings{ZarriessSeeker2008,
  author    = {Zarrieß, Sina and Seeker, Wolfgang},
  title     = {Finite-state rule deduction for parsing non-constituent coordination},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-27254},
  year      = {2008},
  abstract  = {In this paper, we present a finite-state approach to constituency and therewith an analysis of coordination phenomena involving so-called non-constituents. We show that non-constituents can be seen as parts of fully-fledged constituents and therefore be coordinated in the same way. We have implemented an algorithm based on finite state automata that generates an LFG grammar assigning valid analyses to non-constituent coordination structures in the German language.},
  language  = {en}
}
@misc{ZarriessSchlangen2019,
  author    = {Zarriess, Sina and Schlangen, David},
  title     = {Objects of Unknown Categories},
  series = {The 57th Annual Meeting of the Association for Computational Linguistics},
  journal   = {The 57th Annual Meeting of the Association for Computational Linguistics},
  publisher = {Association for Computational Linguistics},
  address   = {Stroudsburg},
  isbn      = {978-1-950737-48-2},
  pages     = {654 -- 659},
  year      = {2019},
  abstract  = {Zero-shot learning in Language \& Vision is the task of correctly labelling (or naming) objects of novel categories. Another strand of work in L\&V aims at pragmatically informative rather than "correct" object descriptions, e.g. in reference games. We combine these lines of research and model zero-shot reference games, where a speaker needs to successfully refer to a novel object in an image. Inspired by models of "rational speech acts", we extend a neural generator to become a pragmatic speaker reasoning about uncertain object categories. As a result of this reasoning, the generator produces fewer nouns and names of distractor categories as compared to a literal speaker. We show that this conversational strategy for dealing with novel objects often improves communicative success, in terms of resolution accuracy of an automatic listener.},
  language  = {en}
}