@inproceedings{bruni-fernandez-2017-adversarial,
    title = "Adversarial evaluation for open-domain dialogue generation",
    author = "Bruni, Elia  and
      Fern{\'a}ndez, Raquel",
    editor = "Jokinen, Kristiina  and
      Stede, Manfred  and
      DeVault, David  and
      Louis, Annie",
    booktitle = "Proceedings of the 18th Annual {SIG}dial Meeting on Discourse and Dialogue",
    month = aug,
    year = "2017",
    address = {Saarbr{\"u}cken, Germany},
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/W17-5534/",
    doi = "10.18653/v1/W17-5534",
    pages = "284--288",
    abstract = "We investigate the potential of adversarial evaluation methods for open-domain dialogue generation systems, comparing the performance of a discriminative agent to that of humans on the same task. Our results show that the task is hard, both for automated models and humans, but that a discriminative agent can learn patterns that lead to above-chance performance."
}