@inproceedings{yu-etal-2021-kontra,
    title = "{K}on{T}ra at {CMCL} 2021 Shared Task: Predicting Eye Movements by Combining {BERT} with Surface, Linguistic and Behavioral Information",
    author = "Yu, Qi  and
      Kalouli, Aikaterini-Lida  and
      Frassinelli, Diego",
    booktitle = "Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics",
    month = jun,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.cmcl-1.15",
    doi = "10.18653/v1/2021.cmcl-1.15",
    pages = "120--124",
    abstract = "This paper describes the submission of the team KonTra to the CMCL 2021 Shared Task on eye-tracking prediction. Our system combines the embeddings extracted from a fine-tuned BERT model with surface, linguistic and behavioral features, resulting in an average mean absolute error of 4.22 across all 5 eye-tracking measures. We show that word length and features representing the expectedness of a word are consistently the strongest predictors across all 5 eye-tracking measures.",
}