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“In addition, Gatt and Krahmer make a distinction between ''objective'' (automatic, corpus-based) and ''subjective'' (human judgements) metrics [164].”
From A Survey of Contrastive and Counterfactual Explanation Generation Methods for Explainable Artificial Intelligence (2021) · cites this paper as [164]
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Self-citationPaleja, R., Silva, A., Chen, L., & Gombolay, M. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1906.06397 · Cited by 14
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Metadata
- Authors
- Hendricks, L. A., Hu, R., Darrell, T., & Akata, Z.
- Affiliations
- University of California, Berkeley (US)
- University of Amsterdam (NL)
- Corresponding author
- Hendricks, Lisa Anne
- Venue
- Lecture notes in computer science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 269-286
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2883512601
- Cited by
- 171
- References
- 36
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 19 · 2023: 19 · 2022: 20 · 2021: 38 · 2020: 34 · 2019: 30 · 2018: 3
- FWCI
- 10.72
- Type
- conference paper
- Language
- en
- Open access
- green
- handle.uba.uva.nl
- Licence
- Locations
- Lecture notes in computer science (publishedVersion)
- UvA-DARE (University of Amsterdam) (publishedVersion, other-oa)
- arXiv (Cornell University) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- Defense Advanced Research Projects Agency
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- counterfactual explanations, fine-grained classification, foil, sentence correction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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