@inproceedings{idahl-etal-2021-towards,
    title = "Towards Benchmarking the Utility of Explanations for Model Debugging",
    author = "Idahl, Maximilian  and
      Lyu, Lijun  and
      Gadiraju, Ujwal  and
      Anand, Avishek",
    editor = "Pruksachatkun, Yada  and
      Ramakrishna, Anil  and
      Chang, Kai-Wei  and
      Krishna, Satyapriya  and
      Dhamala, Jwala  and
      Guha, Tanaya  and
      Ren, Xiang",
    booktitle = "Proceedings of the First Workshop on Trustworthy Natural Language Processing",
    month = jun,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2021.trustnlp-1.8/",
    doi = "10.18653/v1/2021.trustnlp-1.8",
    pages = "68--73",
    abstract = "Post-hoc explanation methods are an important class of approaches that help understand the rationale underlying a trained model`s decision. But how useful are they for an end-user towards accomplishing a given task? In this vision paper, we argue the need for a benchmark to facilitate evaluations of the utility of post-hoc explanation methods. As a first step to this end, we enumerate desirable properties that such a benchmark should possess for the task of debugging text classifiers. Additionally, we highlight that such a benchmark facilitates not only assessing the effectiveness of explanations but also their efficiency."
}