Evaluation Cards for XAI Metrics

Rokas Gipiškis; Olga Kurasova

Evaluation Cards for XAI Metrics

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Abstract

The evaluation of explainable AI (XAI) methods is affected by a lack of standardization. Metrics are inconsistently defined, incompletely reported, and rarely validated against common baselines. In this paper, we identify transparency of evaluation reporting as a central, under-addressed problem. We propose the XAI Evaluation Card, a documentation template analogous to model cards, designed to accompany any study that introduces an XAI evaluation metric. The card covers explicit declaration of target properties, grounding levels, metric assumptions, validation evidence, gaming risks, and known failure cases. We argue that adopting this template as a community norm would reduce evaluation fragmentation, support meta-analysis, and improve accountability in XAI research.

Anthology ID:: 2026.evaleval-1.39
Volume:: Proceedings of the Workshop on Evaluating Evaluations (EvalEval)
Month:: July
Year:: 2026
Address:: San Diego, CA
Editors:: Mubashara Akhtar, Jan Batzner, Leshem Choshen, Avijit Ghosh, Usman Gohar, Jennifer Mickel, Ichhya Pant, Zeerak Talat, Michelle Lin
Venues:: EvalEval | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 245–251
Language:
URL:: https://aclanthology.org/2026.evaleval-1.39/
DOI:
Bibkey:
Cite (ACL):: Rokas Gipiškis and Olga Kurasova. 2026. Evaluation Cards for XAI Metrics. In Proceedings of the Workshop on Evaluating Evaluations (EvalEval), pages 245–251, San Diego, CA. Association for Computational Linguistics.
Cite (Informal):: Evaluation Cards for XAI Metrics (Gipiškis & Kurasova, EvalEval 2026)
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PDF:: https://aclanthology.org/2026.evaleval-1.39.pdf

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@inproceedings{gipiskis-kurasova-2026-evaluation,
    title = "Evaluation Cards for {XAI} Metrics",
    author = "Gipi{\v{s}}kis, Rokas  and
      Kurasova, Olga",
    editor = "Akhtar, Mubashara  and
      Batzner, Jan  and
      Choshen, Leshem  and
      Ghosh, Avijit  and
      Gohar, Usman  and
      Mickel, Jennifer  and
      Pant, Ichhya  and
      Talat, Zeerak  and
      Lin, Michelle",
    booktitle = "Proceedings of the Workshop on Evaluating Evaluations ({E}val{E}val)",
    month = jul,
    year = "2026",
    address = "San Diego, CA",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.evaleval-1.39/",
    pages = "245--251",
    ISBN = "979-8-89176-429-3",
    abstract = "The evaluation of explainable AI (XAI) methods is affected by a lack of standardization. Metrics are inconsistently defined, incompletely reported, and rarely validated against common baselines. In this paper, we identify transparency of evaluation reporting as a central, under-addressed problem. We propose the XAI Evaluation Card, a documentation template analogous to model cards, designed to accompany any study that introduces an XAI evaluation metric. The card covers explicit declaration of target properties, grounding levels, metric assumptions, validation evidence, gaming risks, and known failure cases. We argue that adopting this template as a community norm would reduce evaluation fragmentation, support meta-analysis, and improve accountability in XAI research."
}

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    <abstract>The evaluation of explainable AI (XAI) methods is affected by a lack of standardization. Metrics are inconsistently defined, incompletely reported, and rarely validated against common baselines. In this paper, we identify transparency of evaluation reporting as a central, under-addressed problem. We propose the XAI Evaluation Card, a documentation template analogous to model cards, designed to accompany any study that introduces an XAI evaluation metric. The card covers explicit declaration of target properties, grounding levels, metric assumptions, validation evidence, gaming risks, and known failure cases. We argue that adopting this template as a community norm would reduce evaluation fragmentation, support meta-analysis, and improve accountability in XAI research.</abstract>
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%0 Conference Proceedings
%T Evaluation Cards for XAI Metrics
%A Gipiškis, Rokas
%A Kurasova, Olga
%Y Akhtar, Mubashara
%Y Batzner, Jan
%Y Choshen, Leshem
%Y Ghosh, Avijit
%Y Gohar, Usman
%Y Mickel, Jennifer
%Y Pant, Ichhya
%Y Talat, Zeerak
%Y Lin, Michelle
%S Proceedings of the Workshop on Evaluating Evaluations (EvalEval)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, CA
%@ 979-8-89176-429-3
%F gipiskis-kurasova-2026-evaluation
%X The evaluation of explainable AI (XAI) methods is affected by a lack of standardization. Metrics are inconsistently defined, incompletely reported, and rarely validated against common baselines. In this paper, we identify transparency of evaluation reporting as a central, under-addressed problem. We propose the XAI Evaluation Card, a documentation template analogous to model cards, designed to accompany any study that introduces an XAI evaluation metric. The card covers explicit declaration of target properties, grounding levels, metric assumptions, validation evidence, gaming risks, and known failure cases. We argue that adopting this template as a community norm would reduce evaluation fragmentation, support meta-analysis, and improve accountability in XAI research.
%U https://aclanthology.org/2026.evaleval-1.39/
%P 245-251

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Markdown (Informal)

[Evaluation Cards for XAI Metrics](https://aclanthology.org/2026.evaleval-1.39/) (Gipiškis & Kurasova, EvalEval 2026)

Evaluation Cards for XAI Metrics (Gipiškis & Kurasova, EvalEval 2026)

ACL

Rokas Gipiškis and Olga Kurasova. 2026. Evaluation Cards for XAI Metrics. In Proceedings of the Workshop on Evaluating Evaluations (EvalEval), pages 245–251, San Diego, CA. Association for Computational Linguistics.