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XKDD 2026 : 8th ECML PKDD International Workshop on eXplainable Knowledge Discovery in Data Mining on the Validation of Explanations | |||||||||
| Link: https://xkdd2026.isti.cnr.it | |||||||||
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Call For Papers | |||||||||
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XKDD and Beyond 2026 - Call for Papers
------------------------------------------------------------------------- 8th ECML PKDD International Workshop on eXplainable Knowledge Discovery in Data Mining on the Validation of Explanations https://xkdd2026.isti.cnr.it/ ------------------------------------------------------------------------- co-located with the ECML-PKDD 2026 Conference, Naples, Italy IMPORTANT DATES Paper Submission deadline: June 5th, 2026 Accept/Reject Notification: July 5th, 2026 Workshop: September 7th, 2026 CONTEXT & OBJECTIVES XKDD (eXplaining Knowledge Discovery in Data Mining) is a workshop dedicated to eXplainable Artificial Intelligence (XAI) in Data Mining, focusing on methods that explain the behavior and outputs of complex Machine Learning models. This edition focuses on the validation of explanation methods. While numerous XAI techniques have been proposed, the field still lacks a clear and widely accepted evaluation strategy, making it difficult to determine which explanations are reliable and informative. For this reason, we invite contributions that examine how explanation methods can be evaluated and compared across models, tasks, and data distributions. We are particularly interested in contributions that analyze the assumptions and limitations of existing evaluation metrics and study their behavior across models, tasks, or data distributions. The interplay with ethical values is also an important topic, such as how reliably XAI methods reflect properties including faithfulness, stability, and usefulness. Beyond quantitative evaluation, the workshop also addresses qualitative validation, including expert analysis and real-world use cases. In high-stakes settings involving sensitive data, numerical metrics alone may not reveal whether explanations are faithful, understandable, or aligned with ethical principles. By focusing on validation as a core component of XAI, XKDD aims to strengthen the methodological foundations of explainability in Data Mining and Machine Learning. TOPICS XKDD 2026 invites researchers and practitioners from academia and industry to explore the latest advancements in explainability, trust, and evaluation of explanation. Join us in shaping the future of ethical and transparent AI-driven decision-making! Topics of interest include, but are not limited to: - XAI and evaluation metrics - Qualitative approaches to validate XAI methods - Quantitative approaches to validate XAI methods - XAI for Trustworthy AI - XAI for Social AI - XAI to Align AI with Human Values - XAI for Outlier and Anomaly Detection - XAI methodologies for tabular data, images, text, and time series - XAI for ethical, fair, and transparent AI systems - XAI techniques for enabling unlearning in machine learning models - The role of XAI in privacy preservation and regulatory compliance - Case studies on XAI and unlearning applications in real-world scenarios - XAI for Federated Learning - XAI for Graph-based Approaches - XAI for Visualization - Interpretable Machine Learning - Transparent Data Mining - XAI for Fairness Checking - Multi-level XAI - Explanation, Accountability, and Liability from an Ethical and Legal Perspective XKDD 2026 is a Workshop of the ECML-PKDD Conference: https://ecmlpkdd.org/2026/ SUBMISSION & PUBLICATION The submission link is: https://cmt3.research.microsoft.com/ECMLPKDDWT2026/Submission/Index (choosing the right track corresponding to XKDD 2026) Papers must be written in English and formatted according to the Springer Lecture Notes in Computer Science (LNCS) guidelines following the style of the main conference (format). The maximum length of either research or position papers is 16 pages references included. Overlength papers will be rejected without review (papers with smaller page margins and font sizes than specified in the author instructions and set in the style files will also be treated as overlength). We also accept 2-4 pages abstracts (including references) that outline new emerging ideas and/or already published work for presentation-only, to stimulate discussion and collaboration among participants Authors who submit their work to XKDD 2026 commit themselves to present their paper at the workshop in case of acceptance. XKDD 2026 considers the author list submitted with the paper as final. No additions or deletions to this list may be made after paper submission, either during the review period, or in case of acceptance, at the final camera ready stage. Condition for inclusion in the post-proceedings is that at least one of the co-authors has presented the paper at the workshop. Pre-proceedings will be available online before the workshop. All accepted full papers will be published as post-proceedings in LNCSI and included in the series name Lecture Notes in Computer Science. More info at: https://xkdd2026.isti.cnr.it/ PROGRAM CO-CHAIRS - Francesca Naretto, University of Pisa, Pisa, Italy - Francesco Spinnato, University of Pisa, Pisa, Italy - Przemyslaw Biecek, Warsaw University of Technology, Poland - Andreas Theissler, Institut für Informatik, Justus Liebig University Giessen, Germany STEERING COMMITTEE - Riccardo Guidotti, University of Pisa, Italy - Anna Monreale, University of Pisa, Italy - Salvatore Rinzivillo, ISTI-CNR, Pisa, Italy - Przemyslaw Biecek, Warsaw University of Technology, Warsaw, Poland VENUE The event will take place at the ECML-PKDD 2026 Conference. CONTACT All inquires should be sent to francesca.naretto@unipi.it, francesco.spinnato@di.unipi.it |
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