Full Description
This book constitutes the refereed proceedings of the 33rd International Conference on Case-Based Reasoning Research and Development, ICCBR 2025, held in Biarritz, France, during June 30-July 3, 2025.
The 30 full papers presented in this volume were carefully reviewed and selected from 81 submissions. The book also contains one invited talk in full-paper lenght. The papers are grouped into the following topical sections: Invited Talk; CBR and Generative AI Synergies; Theoretical or Methodological CBR Research; and Applied CBR Research.
Contents
.- Invited Talk.
.- EXAR: A Unified Experience-Grounded Agentic Reasoning Architecture.
.- CBR and Generative AI Synergies.
.- AlignLLM: Alignment-based Evaluation using Ensemble of LLMs-as-Judges for Q&A.
.- Visual Question Answering to Generate Case-Based Explanations for Image Classification.
.- Integrating Case-Based Reasoning with LLM for Expense Fraud Detection.
.- LLM-Driven Case-Base Populating for Structuring and Integrating Restoration Experiences.
.- Explaining Translational Embedding Models in Recommender Systems Using Knowledge Graphs and Language Models.
.- Fuzzy Symbolic Reasoning for few-shot KBQA: A CBR-inspired Generative Approach.
.- Context Driven Multi-Query Resolution using LLM-RAG to support the Revision of Explainability needs.
.- LLsiM: Large Language Models for Similarity Assessment in Case-Based Reasoning.
.- Offline-to-Online: Case-Based Knowledge Distillation with Large Language Models for Reinforcement Learning.
.- Utilizing the Structure of Process Models for Guided Generation of Explanatory Texts.
.- Case-Based Reasoning in Generative Agents: Review and Prospect.
.- Theoretical or Methodological CBR Research.
.- Evaluating Objective Metrics for Time Series Model Explainability.
.- A Knowledge Representation Approach for Reasoning with Adaptation Rules.
.- Efficient Case Retrieval Using Dropout Similarity Highway Multigraphs.
.- Advanced Search Techniques for Determining Optimal Sequences of Adaptation Rules in Process-Oriented Case-Based Reasoning.
.- A Framework for Supporting the Iterative Design of CBR Applications.
.- Two-Agent Case-Based Reasoning for Prediction.
.- Towards Non-Programmed Robotic Manipulation of Novel Tasks using GA-driven CBR.
.- Fast Locality Sensitive Hashing with Theoretical Guarantee.
.- Learning CaseØstrem Features with Proxy-Guided Deep Neural Networks.
.- Integration of Time Series Embedding for Efficient Retrieval in Case-Based Reasoning.
.- Extracting Features with Deep Learning for Ensemble-Driven Case-Based Classification.
.- Applied CBR Research.
.- CBRinR Multitask Multiomics Case-based Reasoning in Bioinformatics.
.- Case-based Causal Reasoning for Elite Sport Training.
.- Representing expert reasoning experience by process cases — Application to the delimitation of mobile genetic elements in bacterial chromosomes.
.- Clinical Decision Support for Skin Tumor Treatment: A Case-Based Reasoning Approach.
.- Analysing the contribution of sequential patterns in CBR for childhood obesity prediction.
.- Case-Based Activity Detection from Segmented Internet of Things Data.
.- Explainable sleep-wake recognition using a twin XCBR system with prototypes to improve retrieval efficiency.
.- Case-Based Reasoning with Diffusion Model for Ransomware Detection.
