@article{AvetisyanLagoVasishth2020,
  author    = {Avetisyan, Serine and Lago, Sol and Vasishth, Shravan},
  title     = {Does case marking affect agreement attraction in comprehension?},
  series = {Journal of memory and language},
  volume    = {112},
  journal   = {Journal of memory and language},
  publisher = {Elsevier},
  address   = {San Diego},
  issn      = {0749-596X},
  doi       = {10.1016/j.jml.2020.104087},
  pages     = {18},
  year      = {2020},
  abstract  = {Previous studies have suggested that distinctive case marking on noun phrases reduces attraction effects in production, i.e., the tendency to produce a verb that agrees with a nonsubject noun. An important open question is whether attraction effects are modulated by case information in sentence comprehension. To address this question, we conducted three attraction experiments in Armenian, a language with a rich and productive case system. The experiments showed clear attraction effects, and they also revealed an overall role of case marking such that participants showed faster response and reading times when the nouns in the sentence had different case. However, we found little indication that distinctive case marking modulated attraction effects. We present a theoretical proposal of how case and number information may be used differentially during agreement licensing in comprehension. More generally, this work sheds light on the nature of the retrieval cues deployed when completing morphosyntactic dependencies.},
  language  = {en}
}
@article{PaapeAvetisyanLagoetal.2021,
  author    = {Paape, Dario and Avetisyan, Serine and Lago, Sol and Vasishth, Shravan},
  title     = {Modeling misretrieval and feature substitution in agreement attraction},
  series = {Cognitive science},
  volume    = {45},
  journal   = {Cognitive science},
  number    = {8},
  publisher = {Wiley-Blackwell},
  address   = {Malden, Mass.},
  issn      = {0364-0213},
  doi       = {10.1111/cogs.13019},
  pages     = {30},
  year      = {2021},
  abstract  = {We present computational modeling results based on a self-paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k-fold cross-validation. We find that our data are better accounted for by an encoding-based model of agreement attraction, compared to a retrieval-based model. A novel methodological contribution of our study is the use of comprehension questions with open-ended responses, so that both misinterpretation of the number feature of the subject phrase and misassignment of the thematic subject role of the verb can be investigated at the same time. We find evidence for both types of misinterpretation in our study, sometimes in the same trial. However, the specific error patterns in our data are not fully consistent with any previously proposed model.},
  language  = {en}
}