8th ECML PKDD International Workshop on

eXplainable Knowledge Discovery in Data Mining

on the Validation of Explanations

September 7th, 2026

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Call for Papers

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:

Submission

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 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.

Important Dates

All deadlines expire on 23:59 AoE.

  • Paper Submission deadline: June 5th, 2026
  • Accept/Reject Notification: July 5th, 2026
  • Camera-ready deadline: July 10th, 2026
  • Workshop: September 7th, 2026 (Full Day)

Organization

Program Chairs

Francesca Naretto

KDD Lab, University of Pisa, Italy

Francesco Spinnato

KDD Lab, University of Pisa, Italy

Przemyslaw Biecek

Warsaw University of Technology, Warsaw, Poland

Andreas Theissler

Institut für Informatik, Justus Liebig University Giessen, Germany

Invited Speakers

Peter Flach

Peter Flach

Professor of Artificial Intelligence, School of Computer Science, University of Bristol

TBD

TBD
Peter Flach holds an M.Sc. from Twente and a Ph.D. from Tilburg. He has been Professor of Artificial Intelligence at the University of Bristol since 2003. He is an internationally leading researcher in mining highly structured data and in the evaluation and improvement of machine learning models using ROC analysis. He has also published on the logic and philosophy of machine learning, and on the combination of logic and probability. He is the author of Simply Logical: Intelligent Reasoning by Example (John Wiley, 1994) and Machine Learning: the Art and Science of Algorithms that Make Sense of Data (Cambridge University Press, 2012). From 2010 to 2020, Prof Flach was Editor-in-Chief of the Machine Learning journal. He was Programme Co-Chair of ILP 1999, ECML 2001, KDD 2009, and ECML PKDD 2012 in Bristol. He is a founding board member, former President, and current Vice-President of the European Association for Data Science. His research has been funded by UKRI, EPSRC, MRC, TSB, and the EU, among others. He is currently Director of the UKRI Centres for Doctoral Training in Interactive Artificial Intelligence and Practice-Oriented Artificial Intelligence. His main expertise is in machine learning, data science, human-centred artificial intelligence, and practice-oriented artificial intelligence.
Georgiana Ifrim

Georgiana Ifrim

Associate Professor, School of Computer Science, University College Dublin

TBD

TBD
Dr. Georgiana Ifrim is an Associate Professor at the School of Computer Science, University College Dublin, Director of the Research Ireland Centre for Research Training in Machine Learning (ML-Labs), and a Funded Investigator with the Insight Centre for Data Analytics. She previously served as Director of Graduate Research at UCD Computer Science, receiving the GEM School Award twice, and was nominated in 2023 for the UCD Graduate Studies Dean’s Award for Excellence in Doctoral Supervision. She holds a PhD and MSc in Computer Science from the Max Planck Institute for Informatics, Germany, and a BSc from the University of Bucharest. Her research focuses on scalable machine learning, data mining, interpretable models for sequential data, including time series, and text mining. She has published over 50 peer-reviewed papers in leading venues such as KDD, ACL, WWW, ICDE, ECML, COLING, TKDE, and DMKD. Dr. Ifrim is a senior editorial board member of the Machine Learning Journal and regularly serves in senior roles for major conferences including AAAI, IJCAI, and ECML-PKDD. Her team develops open-source software and industry research prototypes, and has won three international data modelling competitions: SNOW 2014, Spectroscopy 2022, and Spectroscopy 2024.

Program Committee

  • Alessio Cascione, University of Pisa
  • Andrea Pugnana, University of Trento
  • Andreas Theissler, Justus Liebig University Giessen
  • Cristiano Landi, University of Pisa
  • Eleonora Cappuccio, University of Pisa
  • Felix Gerschner, Justus Liebig University Giessen
  • Francesca Naretto, University of Pisa
  • Francesco Spinnato, University of Pisa
  • Giacomo Fidone, University of Pisa
  • Lorenzo Mannocci, University of Pisa
  • Luca Corbucci, Bruno Kessler Foundation
  • Marta Marchiori Manerba, University of Turin
  • Martina Cinquini, University of Pisa
  • Przemyslaw Biecek, Warsaw University of Technology
  • Simone Piaggesi, University of Pisa
  • Valerio Bonsignori, Scuola Normale Superiore

TBD

Venue

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

Partners

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.

Contacts

All inquires should be sent to

francesca.naretto@unipi.it

francesco.spinnato@unipi.it