| 2023 | A Twin XCBR System Using Supportive and Contrastive Explanations. | Betl Bayrak, Kerstin Bach |
| 2023 | Beyond Post-Hoc Instance-Based Explanation Methods. | Betl Bayrak |
| 2023 | Case-Based Cleaning of Text Images. | Eric Astier, Hugo Iopeti, Jean Lieber, Hugo Mathieu Steinbach, Ludovic Yvoz |
| 2022 | Extraction of analogies between sentences on the level of syntax using parse trees. | Yifei Zhou, Rashel Fam, Yves Lepage |
| 2022 | Generating Counterfactual Images: Towards a C2C-VAE Approach. | Ziwei Zhao, David Leake, Xiaomeng Ye, David J. Crandall |
| 2022 | Towards Experience-based Assistance for Personal Robotic Process Automation by Process-Oriented Case-based Reasoning. | Christian Zeyen, Rudolf Koch, Sven Schwarz, Heiko Maus, Ralph Bergmann |
| 2022 | Case Adaptation with Neural Networks: Capabilities and Limitations. | Xiaomeng Ye, David Leake, David Crandall |
| 2022 | Leveraging SHAP and CBR for Dimensionaltiy Reduction on the Psychology Prediction Dataset. | Zachary Wilkerson, David Leake, David Crandall |
| 2022 | DL-CBR Hybridization for Feature Generation and Similarity Assessment. | Zachary Wilkerson |
| 2022 | Towards efficient scoring of student-generated long-form analogies in STEM. | Thilini Wijesiriwardene, Ruwan Wickramarachchi, Valerie L. Shalin, Amit P. Sheth |
| 2022 | How Close Is Too Close? The Role of Feature Attributions in Discovering Counterfactual Explanations. | Anjana Wijekoon, Nirmalie Wiratunga, Ikechukwu Nkisi-Orji, Chamath Palihawadana, David Corsar, Kyle Martin |
| 2022 | "Better" Counterfactuals, Ones People Can Understand: Psychologically-Plausible Case-Based Counterfactuals Using Categorical Features for Explainable AI (XAI). | Greta Warren, Barry Smyth, Mark T. Keane |
| 2022 | Counterfactual Explanations for eXplainable AI (XAI). | Greta Warren |
| 2022 | CBR-foX: A generic post-hoc case-based reasoning method for the explanation of time-series forecasting. | Moiss Fernando Valdez-vila, Gerardo Arturo Prez-Prez, Humberto Sarabia-Osorio, Carlos Bermejo-Sabbagh, Mauricio Gabriel Orozco-del-Castillo |
| 2022 | A Case-based Explanation Method for Weather Forecasting. | Moiss Fernando Valdez-vila, Gerardo Arturo Prez-Prez, Humberto Sarabia-Osorio, Carlos Bermejo-Sabbagh, Mauricio Gabriel Orozco-del-Castillo |
| 2022 | A Case-Based Approach for Content Planning in Data-to-Text Generation. | Ashish Upadhyay, Stewart Massie |
| 2022 | CBR For Interpretable Response Selection In Conversational Modelling. | Malavika Sureah |
| 2022 | IREX: A reusable process for the iterative refinement and explanation of classification models. | Christian E. Sosa-Espadas, Manuel Cetina-Aguilar, Jose A. Soladrero, Jesus M. Darias, Esteban E. Brito-Borges, Nora L. Cuevas-Cuevas, Mauricio Gabriel Orozco-del-Castillo |
| 2022 | Applying explanation methods for the iterative refinement of an ANN-based depression screening tool. | Christian E. Sosa-Espadas, Manuel Cetina-Aguilar, Jose A. Soladrero, Jesus M. Darias, Esteban E. Brito-Borges, Nora L. Cuevas-Cuevas, Mauricio Gabriel Orozco-del-Castillo |
| 2022 | A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations. | Barry Smyth, Mark T. Keane |
| 2022 | Addressing Trust and Mutability Issues in XAI utilising Case Based Reasoning. | Pedram Salimi |
| 2022 | The Application of Qualitative Metadata to Analogical Reasoning. | Dave Ragget |
| 2022 | Explainable Weather Forecasts Through an LSTM-CBR Twin System. | Craig Pirie, Malavika Suresh, Pedram Salimi, Chamath Palihawadana, Gayani Nanayakkara |
| 2022 | Explaining and Upsampling Anomalies in Time-Series Sensor Data. | Craig Pirie |
| 2022 | Developing a Decision Support System leveraging Distributed and Heterogeneous Sources: Case-Based Reasoning for Manufacturing Incident Handling. | M. van der Pas |