Sixth Workshop on XCBR:
Case-Based Reasoning for the Explanation of Intelligent Systems

CALL FOR PAPERS

XCBR workshop at ICCBR aims to provide a medium of exchange for information about trends, research issues and practical experiences in the use of Case-Based Reasoning (CBR) for the inclusion of explanations to several AI techniques (including CBR itself).  CBR provides opportunities for exploiting memory-based techniques to generate these explanations that can be successfully applied to the explanation of emerging AI and machine learning techniques.

The problem of explainability in Artificial Intelligence is not new but the rise of the autonomous intelligent systems has created the necessity to understand how these intelligent systems achieve a solution, make a prediction or a recommendation or reason to support a decision 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”.

For this purpose, the XCBR workshop helps an exchange of ideas and interaction, suited to highlight the main bottlenecks and challenges, as well as the more promising research lines, for CBR research related to the explanation of intelligent systems.

SUBMISSIONS: SCOPE OF THE WORKSHOP

Research contributions submitted to the workshop will be related to areas that include, but are not limited to, the following:

• AI explanation methods using CBR: CBR explanations of ML techniques, planning, recommender systems, 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. carrying out the new AI law in the EU).
• Interfaces to show 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 on explainability.

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. the submission will be via the EasyChair system. The CEUR-WS is the format required for the final camera-ready copy, please use the required LaTeX template from CEUR-WS.

IMPORTANT DATES

SCHEDULE (tentative – to be updated)

PARTICIPATION IN THE WORKSHOP 

This workshop will be held on July 1st, 2024 as part of the ICCBR 2024 workshop series in Merida, Mexico. 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

Anne Liret, BT France, France   anne.liret@bt.com

XCBR’24 will have the support of the European Project iSee (Intelligent Sharing of Explanation Experiences, https://isee4xai.com) participated by several members of ICCBR Program Committee.

XCBR PROGRAM COMMITTEE

• Belén Díaz Agudo, University Complutense of Madrid, Spain
• Marta Caro Martinez, University Complutense of Madrid, Spain
• Juan A. Recio García, University Complutense of Madrid, Spain
• Nirmalie Wiratunga, Robert Gordon University, UK
• Derek Bridge, University College Cork, Ireland
• Rosina Weber, Drexel University, USA
• Mark Keane, University College Dublin, Ireland
• David Leake, Indiana University, USA
• Anjana Wijekoon, University College London, UK
• Kyle Martin, Robert Gordon University, UK
• Ikechukwu Nkisi-Orji, Robert Gordon University, UK
• Anne Liret, BT France, France
• Bruno Fleisch, BT France, France