@inproceedings{sadeghi-scheutz-2018-sensitivity,
    title = "Sensitivity to Input Order: Evaluation of an Incremental and Memory-Limited {B}ayesian Cross-Situational Word Learning Model",
    author = "Sadeghi, Sepideh  and
      Scheutz, Matthias",
    editor = "Bender, Emily M.  and
      Derczynski, Leon  and
      Isabelle, Pierre",
    booktitle = "Proceedings of the 27th International Conference on Computational Linguistics",
    month = aug,
    year = "2018",
    address = "Santa Fe, New Mexico, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/C18-1268/",
    pages = "3170--3180",
    abstract = "We present a variation of the incremental and memory-limited algorithm in (Sadeghi et al., 2017) for Bayesian cross-situational word learning and evaluate the model in terms of its functional performance and its sensitivity to input order. We show that the functional performance of our sub-optimal model on corpus data is close to that of its optimal counterpart (Frank et al., 2009), while only the sub-optimal model is capable of predicting the input order effects reported in experimental studies."
}