@inproceedings{xia-etal-2020-bert,
    title = "Which *{BERT}? {A} Survey Organizing Contextualized Encoders",
    author = "Xia, Patrick  and
      Wu, Shijie  and
      Van Durme, Benjamin",
    editor = "Webber, Bonnie  and
      Cohn, Trevor  and
      He, Yulan  and
      Liu, Yang",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2020.emnlp-main.608/",
    doi = "10.18653/v1/2020.emnlp-main.608",
    pages = "7516--7533",
    abstract = "Pretrained contextualized text encoders are now a staple of the NLP community. We present a survey on language representation learning with the aim of consolidating a series of shared lessons learned across a variety of recent efforts. While significant advancements continue at a rapid pace, we find that enough has now been discovered, in different directions, that we can begin to organize advances according to common themes. Through this organization, we highlight important considerations when interpreting recent contributions and choosing which model to use."
}