| 2026 | ICCBR | Combining Deep Learning and Large Language Models for Retrieval-Based Image Classification. | Zachary Wilkerson, David Leake, David Crandall |
| 2025 | ICCBR | Learning Case Features with Proxy-Guided Deep Neural Networks. | Vibhas Vats, Zachary Wilkerson, Hiroki Sato, David Leake, David Crandall |
| 2025 | ICCBR | Extracting Features with Deep Learning for Ensemble-Driven Case-Based Classification. | Zachary Wilkerson, David Leake, David Crandall, Benjamin Wilkerson |
| 2024 | ICCBR | Extracting Indexing Features for CBR from Deep Neural Networks: A Transfer Learning Approach. | Zachary Wilkerson, David Leake, Vibhas Vats, David Crandall |
| 2023 | ICCBR | Examining the Impact of Network Architecture on Extracted Feature Quality for CBR. | David Leake, Zachary Wilkerson, Vibhas Vats, Karan Acharya, David J. Crandall |
| 2023 | ICCBR | Exploring Deep Learning-Based Feature Extraction for Case-Based Reasoning Retrieval. | Zachary Wilkerson |
| 2022 | ICCBR | Extracting Case Indices from Convolutional Neural Networks: A Comparative Study. | David Leake, Zachary Wilkerson, David Crandall |
| 2022 | ICCBR | DL-CBR Hybridization for Feature Generation and Similarity Assessment. | Zachary Wilkerson |
| 2022 | ICCBR | Leveraging SHAP and CBR for Dimensionaltiy Reduction on the Psychology Prediction Dataset. | Zachary Wilkerson, David Leake, David Crandall |
| 2021 | ICCBR | On Combining Knowledge-Engineered and Network-Extracted Features for Retrieval. | Zachary Wilkerson, David Leake, David J. Crandall |