@inproceedings{pereira-etal-2017-lexical,
    title = "Lexical Simplification with the Deep Structured Similarity Model",
    author = "Pereira, Lis  and
      Liu, Xiaodong  and
      Lee, John",
    editor = "Kondrak, Greg  and
      Watanabe, Taro",
    booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
    month = nov,
    year = "2017",
    address = "Taipei, Taiwan",
    publisher = "Asian Federation of Natural Language Processing",
    url = "https://preview.aclanthology.org/corrections-2025-06/I17-2073/",
    pages = "430--435",
    abstract = "We explore the application of a Deep Structured Similarity Model (DSSM) to ranking in lexical simplification. Our results show that the DSSM can effectively capture fine-grained features to perform semantic matching when ranking substitution candidates, outperforming the state-of-the-art on two standard datasets used for the task."
}