• Corpus ID: 240354726

On Quantitative Evaluations of Counterfactuals

@article{Hvilshj2021OnQE,
  title={On Quantitative Evaluations of Counterfactuals},
  author={Frederik Hvilsh{\o}j and Alexandros Iosifidis and Ira Assent},
  journal={ArXiv},
  year={2021},
  volume={abs/2111.00177}
}
As counterfactual examples become increasingly popular for explaining decisions of deep learning models, it is essential to understand what properties quantitative evaluation metrics do capture and equally important what they do not capture. Currently, such understanding is lacking, potentially slowing down scientific progress. In this paper, we consolidate the work on evaluating visual counterfactual examples through an analysis and experiments. We find that while most metrics behave as… 

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