Call for Papers

The XCBR workshop at ICCBR 2025 aims to provide a platform for exchanging recent work on trends, research challenges, and practical experiences in the use of Case-Based Reasoning (CBR) for incorporating explanations into various AI techniques (including CBR itself). CBR offers opportunities to leverage memory-based techniques to generate explanations that can be successfully applied to emerging AI and machine learning techniques.

The challenge of explainability in Artificial Intelligence is not new. Still, the rise of autonomous intelligent systems has made it essential to understand how such systems achieve solutions, make predictions, issue recommendations, or reason to support decisions to increase users' trust in these systems. The goal of Explainable Artificial Intelligence (XAI) is “to create a suite of new or modified machine learning techniques that produce explainable models that, when combined with effective explanation techniques, enable end users to understand, appropriately trust, and effectively manage the emerging generation of Artificial Intelligence (AI) systems”.

In 2025, we will expand our focus to include ethical and regulatory aspects of AI, exploring not just explainability but also topics such as algorithmic fairness, privacy, and accountability. Given the increasing attention to AI regulation, we will discuss the impact of new laws, such as the EU’s AI Act, and how such regulations might shape the development of more transparent and responsible techniques. Incorporating ethical frameworks into AI systems is now a priority, and this workshop will serve as a space to reflect on how CBR can contribute to this field.

The workshop fosters an exchange of ideas and interaction, highlighting the main bottlenecks and challenges as well as the most promising research lines in CBR research related to the explanation of intelligent systems.

We invite researchers and practitioners to submit their research contributions on topics that include, but are not limited to, the following:

• AI explanation methods using CBR: CBR explanations of ML techniques, planning, recommender systems, and decision-making techniques.

• Explanations of complex CBR systems.

• Hybrid CBR models to provide explanation capabilities.

• Generative AI and XCBR.

• Evaluation metrics, methods, and measures for XAI and XCBR.

• Case-based explanation capabilities for different domains.

• Ethics and legal regulation of AI (e.g., implementing the new AI law in the EU).

• Visualizations for case-based explanations.

• Lessons learned in XCBR investigations.

• Challenge tasks for XCBR systems in novel AI techniques.

• User interaction for explanations.

• The role of experience in explainability.

We also invite researchers, academics, and professionals to submit their proposals to engage in this interdisciplinary dialogue on how CBR and XAI can contribute to developing more explainable and ethical AI systems.

Submission Procedure and Format

We invite submissions of two types: 

1. Long research and application papers: with at least 10 up to 16 pages, including references.

2. Short position papers: with at least 5 up to 9 pages, including references.

Papers must be submitted in electronic form as PDF through EasyChair. The CEUR-WS is the format required for the final camera-ready copy. Please use the LaTeX template from CEUR-WS.

Important Dates

• Paper submission deadline: April 21 2025

• Notification of acceptance: April 28 2025

• Camera-ready submission: May 1 2025

• Workshop date: June 30 2025

Participation in the Workshop

This workshop will be held in Biarritz (France) as part of the ICCBR 2025 workshop series. This workshop is open to all interested conference participants. The Organizing Committee will select a subset of the submitted papers for oral presentation.

Workshop Chairs

• Marta Caro-Martínez, Complutense University of Madrid, Spain (martcaro@ucm.es)

• Belén Díaz-Agudo, Complutense University of Madrid, Spain (belend@ucm.es)

• Kerstin Bach, Norwegian University of Science and Technology, Norway (kerstin.bach@ntnu.no)

• Ikechukwu Nkisi-Orji, Robert Gordon University, United Kingdom (i.nkisi-orji@rgu.ac.uk)

Workshop Program Committee (TBC)