-- Integrating kNN Retrieval with Inference on Graphical Models in Case-Based Reasoning. -- Updating Global Similarity Measures in Learning CBR Systems. -- Even-Ifs From If-Onlys: Are the Best Semi-Factual Explanations Found Using Counterfactuals As Guides?. -- Improving Complex Adaptations in Process-Oriented Case-Based Reasoning by Applying Rule-Based Adaptation. -- Visualization of similarity models for CBR comprehension and maintenance. -- Use Case-Specific Reuse of XAI Strategies: Design and Analysis Through An Evaluation Metrics Library. -- An Empirical Analysis of User Preferences Regarding XAI metrics. -- CBR-Ren: A Case-Based Reasoning Driven Retriever-Generator Model for Hybrid Long-form Numerical Reasoning. -- A Case-based Reasoning and Explaining Model for Temporal Point Process. -- Extracting Indexing Features for CBR from Deep Neural Networks: A Transfer Learning Approach. -- Ensemble Stacking Case-Based Reasoning for Regression. -- Retrieval Augmented Generation with LLMs for Explaining Business Process Models. -- The Intelligent Tutoring System AI-VT with Case-Based Reasoning and Real Time Recommender Models. -- Explaining Multiple Instances Counterfactually: User Tests of Group-Counterfactuals for XAI. -- Olaaaf: a General Adaptation Prototype. -- Identifying Missing Sensor Values in IoT Time Series Data: A Weight-Based Extension of Similarity Measures for Smart Manufacturing. -- Examining the potential of sequence patterns from EEG data as alternative case representation for seizure detection. -- Towards a Case-Based Support for Responding Emergency Calls. -- CBRkit: An Intuitive Case-Based Reasoning Toolkit for Python. -- Experiential questioning for VQA. -- Autocompletion of Architectural Spatial Configurations using Case-Based Reasoning, Graph Clustering, and Deep Learning. -- A Case-Based Reasoning Approach to Post-Injury Training. -- Towards Network Implementation of CBR: Case Study of a Neural Network K-NN Algorithm. -- Aligning to Human Decision-Makers in Military Medical Triage. -- Counterfactual-Based Synthetic Case Generation. -- On Implementing Case-Based Reasoning with Large Language Models. -- Using Case-Based Causal Reasoning to Provide Explainable Counterfactual Diagnosis in Personalized Sprint Training. -- Item-Specific Similarity Assessments for Explainable Depression Screening. -- CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering.

This book constitutes the refereed proceedings of the 32nd International Conference on Case-Based Reasoning Research and Development, ICCBR 2024, held in Merida, Mexico, during July 1-4, 2024. The 29 full papers included in this book were carefully reviewed and selected from 91 submissions. They cover a wide range of CBR topics of interest both to practitioners and researchers, including: improvements to the CBR methodology itself: case representation, similarity, retrieval, adaptation, etc.; synergies with other Artificial Intelligence topics, such as Explainable AI and Large Language Models; and finally a whole catalog of applications to different domains such as health-care, education, and legislation.