@inproceedings{rotaru-2021-andi,
    title = "{ANDI} at {S}em{E}val-2021 Task 1: Predicting complexity in context using distributional models, behavioural norms, and lexical resources",
    author = "Rotaru, Armand",
    editor = "Palmer, Alexis  and
      Schneider, Nathan  and
      Schluter, Natalie  and
      Emerson, Guy  and
      Herbelot, Aurelie  and
      Zhu, Xiaodan",
    booktitle = "Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2021.semeval-1.84/",
    doi = "10.18653/v1/2021.semeval-1.84",
    pages = "655--660",
    abstract = "In this paper we describe our participation in the Lexical Complexity Prediction (LCP) shared task of SemEval 2021, which involved predicting subjective ratings of complexity for English single words and multi-word expressions, presented in context. Our approach relies on a combination of distributional models, both context-dependent and context-independent, together with behavioural norms and lexical resources."
}