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 of interest include, but are not limited to:
Electronic submissions will be handled via CMT.
Papers must be written in English and formatted according to the Springer Lecture Notes in Computer Science (LNCS) guidelines, using the same format as the main conference.
The maximum length for both research papers and position papers is 16 pages, including references. Overlength papers will be rejected without review. Papers with smaller margins or font sizes than those specified in the author instructions and style files will also be treated as overlength.
We also accept full papers and 2 to 4 page abstracts, including references, for presentation only. These submissions may outline new emerging ideas and/or already published work, with the aim of stimulating discussion and collaboration among participants.
Authors who submit their work to XKDD 2026 commit to presenting their paper at the workshop if it is accepted. XKDD 2026 considers the author list submitted with the paper to be final. No additions or deletions may be made after submission, either during the review period or, in case of acceptance, at the final camera-ready stage.
When submitting a paper, authors should indicate in a note whether they wish to opt out of publication in the post-proceedings if the paper is accepted. All accepted full papers whose authors do not opt out will be published in the post-proceedings as part of the Lecture Notes in Computer Science series.
A condition for inclusion in the post-proceedings is that at least one co-author presents the paper at the workshop. Pre-proceedings will be made available online before the workshop.
All deadlines expire on 23:59 AoE.
The event will take place at the ECML-PKDD 2026 Conference, Room TBD.
Additional information about the location can be found at
the main conference web page: ECML-PKDD 2026
This workshop is partially supported by the European Community H2020 Program under research and innovation programme, grant agreement 834756 XAI, science and technology for the explanation of ai decision making.
This workshop is partially supported by TANGO. TANGO is a €7M EU-funded Horizon Europe project that aims to develop the theoretical foundations and the computational framework for synergistic human-machine decision making. The 4-year project will pave the way for the next generation of human-centric AI systems. TANGO.
This workshop is partially supported by the European Community NextGenerationEU programme under the funding schemes PNRR-PE-AI FAIR (Future Artificial Intelligence Research). FAIR.
This workshop has been partially supported by the Italian Project Fondo Italiano per la Scienza FIS00001966 ``MIMOSA''. MIMOSA.
The XKDD event was organised as part of the SoBigData.it project (Prot. IR0000013 - Call n. 3264 of 12/28/2021) initiatives aimed at training new users and communities in the usage of the research infrastructure (SoBigData.eu). “SoBigData.it receives funding from European Union – NextGenerationEU – National Recovery and Resilience Plan (Piano Nazionale di Ripresa e Resilienza, PNRR) – Project: “SoBigData.it – Strengthening the Italian RI for Social Mining and Big Data Analytics” – Prot. IR0000013 – Avviso n. 3264 del 28/12/2021.” SoBigData.it.
All inquires should be sent to
francesca.naretto@unipi.it
francesco.spinnato@unipi.it
