@inproceedings{huang-etal-2020-counterfactually,
    title = "Counterfactually-Augmented {SNLI} Training Data Does Not Yield Better Generalization Than Unaugmented Data",
    author = "Huang, William  and
      Liu, Haokun  and
      Bowman, Samuel R.",
    editor = "Rogers, Anna  and
      Sedoc, Jo{\~a}o  and
      Rumshisky, Anna",
    booktitle = "Proceedings of the First Workshop on Insights from Negative Results in NLP",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2020.insights-1.13/",
    doi = "10.18653/v1/2020.insights-1.13",
    pages = "82--87"
}