{"total":22,"rows":[{"id":"2405.19074","title":"Resurrecting Old Classes with New Data for Exemplar-Free Continual Learning","created":"2024-05-29","cited_by_count":33,"area":null},{"id":"2503.23283","title":"Language Guided Concept Bottleneck Models for Interpretable Continual Learning","created":"2025-03-30","cited_by_count":28,"area":null},{"id":"2308.08162","title":"Interpretability Benchmark for Evaluating Spatial Misalignment of Prototypical Parts Explanations","created":"2023-08-16","cited_by_count":27,"area":null},{"id":"2312.17004","title":"Continual Learning in Medical Image Analysis: A Comprehensive Review of Recent Advancements and Future Prospects","created":"2023-12-28","cited_by_count":22,"area":null},{"id":"2501.15638","title":"A Comprehensive Survey on Self-Interpretable Neural Networks","created":"2025-01-26","cited_by_count":18,"area":null},{"id":"2405.14331","title":"LucidPPN: Unambiguous Prototypical Parts Network for User-centric Interpretable Computer Vision","created":"2024-05-23","cited_by_count":15,"area":null},{"id":"2503.00823","title":"Task-Agnostic Guided Feature Expansion for Class-Incremental Learning","created":"2025-03-02","cited_by_count":15,"area":null},{"id":"2503.01087","title":"Rashomon Sets for Prototypical-Part Networks: Editing Interpretable Models in Real-Time","created":"2025-03-03","cited_by_count":13,"area":null},{"id":"2402.06330","title":"Continual Learning on Graphs: A Survey","created":"2024-02-09","cited_by_count":12,"area":null},{"id":"2404.00983","title":"Continual Learning for Smart City: A Survey","created":"2024-04-01","cited_by_count":9,"area":null},{"id":"2409.10329","title":"InfoDisent: Explainability of Image Classification Models by Information Disentanglement","created":"2024-09-16","cited_by_count":8,"area":null},{"id":"2312.08888","title":"Read Between the Layers: Leveraging Multi-Layer Representations for Rehearsal-Free Continual Learning with Pre-Trained Models","created":"2023-12-13","cited_by_count":7,"area":null},{"id":"2507.19321","title":"SIDE: Sparse Information Disentanglement for Explainable Artificial Intelligence","created":"2025-07-25","cited_by_count":4,"area":null},{"id":"2502.09340","title":"This looks like what? Challenges and Future Research Directions for Part-Prototype Models","created":"2025-02-13","cited_by_count":3,"area":null},{"id":"2306.07218","title":"A Protocol for Continual Explanation of SHAP","created":"2023-06-12","cited_by_count":2,"area":null},{"id":"2311.15335","title":"TORE: Token Recycling in Vision Transformers for Efficient Active Visual Exploration","created":"2023-11-26","cited_by_count":2,"area":null},{"id":"2502.20393","title":"Walking the Web of Concept-Class Relationships in Incrementally Trained Interpretable Models","created":"2025-02-27","cited_by_count":1,"area":null},{"id":"2512.07981","title":"CIP-Net: Continual Interpretable Prototype-based Network","created":"2025-12-08","cited_by_count":1,"area":null},{"id":"2602.06592","title":"ProtoQuant: Quantization of Prototypical Parts For General and Fine-Grained Image Classification","created":"2026-02-06","cited_by_count":0,"area":null},{"id":"2604.14519","title":"CI-CBM: Class-Incremental Concept Bottleneck Model for Interpretable Continual Learning","created":"2026-04-16","cited_by_count":0,"area":null},{"id":"2605.11742","title":"Online Continual Learning with Dynamic Label Hierarchies","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2607.19382","title":"Challenges of Explainability in Continual Learning for Time Series Forecasting","created":"2026-07-01","cited_by_count":0,"area":null}],"next_cursor":null}