{"total":34,"rows":[{"id":"2302.00487","title":"A Comprehensive Survey of Continual Learning: Theory, Method and Application","created":"2023-01-31","cited_by_count":872,"area":null},{"id":"2204.04662","title":"FOSTER: Feature Boosting and Compression for Class-Incremental Learning","created":"2022-04-10","cited_by_count":229,"area":null},{"id":"2302.03648","title":"Class-Incremental Learning: A Survey","created":"2023-02-07","cited_by_count":209,"area":null},{"id":"2303.07338","title":"Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need","created":"2023-03-13","cited_by_count":184,"area":null},{"id":"2205.13218","title":"A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning","created":"2022-05-26","cited_by_count":154,"area":null},{"id":"2203.06953","title":"Forward Compatible Few-Shot Class-Incremental Learning","created":"2022-03-14","cited_by_count":127,"area":null},{"id":"2309.14062","title":"FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning","created":"2023-09-25","cited_by_count":87,"area":null},{"id":"2112.12533","title":"PyCIL: A Python Toolbox for Class-Incremental Learning","created":"2021-12-23","cited_by_count":83,"area":null},{"id":"2309.07117","title":"PILOT: A Pre-Trained Model-Based Continual Learning Toolbox","created":"2023-09-13","cited_by_count":64,"area":null},{"id":"2303.14042","title":"Class-Incremental Exemplar Compression for Class-Incremental Learning","created":"2023-03-24","cited_by_count":50,"area":null},{"id":"2407.14143","title":"Class-Incremental Learning with CLIP: Adaptive Representation Adjustment and Parameter Fusion","created":"2024-07-19","cited_by_count":47,"area":null},{"id":"2310.05719","title":"Transformer Fusion with Optimal Transport","created":"2023-10-09","cited_by_count":36,"area":null},{"id":"2308.02346","title":"Class Incremental Learning with Self-Supervised Pre-Training and Prototype Learning","created":"2023-08-04","cited_by_count":18,"area":null},{"id":"2308.01746","title":"Neural Collapse Terminus: A Unified Solution for Class Incremental Learning and Its Variants","created":"2023-08-03","cited_by_count":14,"area":null},{"id":"2208.12967","title":"Anti-Retroactive Interference for Lifelong Learning","created":"2022-08-27","cited_by_count":13,"area":null},{"id":"2302.14475","title":"Benchmarking Deepart Detection","created":"2023-02-28","cited_by_count":12,"area":null},{"id":"2504.13822","title":"Parameter-Efficient Continual Fine-Tuning: A Survey","created":"2025-04-18","cited_by_count":11,"area":null},{"id":"2402.07839","title":"Towards Meta-Pruning via Optimal Transport","created":"2024-02-12","cited_by_count":8,"area":null},{"id":"2407.14029","title":"PASS++: A Dual Bias Reduction Framework for Non-Exemplar Class-Incremental Learning","created":"2024-07-19","cited_by_count":8,"area":null},{"id":"2309.09122","title":"FDCNet: Feature Drift Compensation Network for Class-Incremental Weakly Supervised Object Localization","created":"2023-09-17","cited_by_count":3,"area":null},{"id":"2211.16780","title":"An Optimal Transport-driven Approach for Cultivating Latent Space in Online Incremental Learning","created":"2022-11-30","cited_by_count":2,"area":null},{"id":"2303.13113","title":"AdaCL:Adaptive Continual Learning","created":"2023-03-23","cited_by_count":2,"area":null},{"id":"2310.11482","title":"Enhancing Plasticity for First Session Adaptation Continual Learning","created":"2023-10-17","cited_by_count":2,"area":null},{"id":"2310.20268","title":"Constructing Sample-to-Class Graph for Few-Shot Class-Incremental Learning","created":"2023-10-31","cited_by_count":2,"area":null},{"id":"2302.00858","title":"Online Continual Learning via the Knowledge Invariant and Spread-out Properties","created":"2023-02-02","cited_by_count":1,"area":null},{"id":"2408.02695","title":"Distribution-Level Memory Recall for Continual Learning: Preserving Knowledge and Avoiding Confusion","created":"2024-08-04","cited_by_count":1,"area":null},{"id":"2504.08412","title":"Boosting the Class-Incremental Learning in 3D Point Clouds via Zero-Collection-Cost Basic Shape Pre-Training","created":"2025-04-11","cited_by_count":1,"area":null},{"id":"2405.15157","title":"Rethinking Class-Incremental Learning from a Dynamic Imbalanced Learning Perspective","created":"2024-05-24","cited_by_count":0,"area":null},{"id":"2407.13768","title":"Addressing Imbalance for Class Incremental Learning in Medical Image Classification","created":"2024-07-18","cited_by_count":0,"area":null},{"id":"2409.05620","title":"Joint Input and Output Coordination for Class-Incremental Learning","created":"2024-09-09","cited_by_count":0,"area":null},{"id":"2503.18672","title":"CalFuse: Multi-Modal Continual Learning via Feature Calibration and Parameter Fusion","created":"2025-03-24","cited_by_count":0,"area":null},{"id":"2506.10489","title":"Class-Incremental Learning for Honey Botanical Origin Classification with Hyperspectral Images: A Study with Continual Backpropagation","created":"2025-06-12","cited_by_count":0,"area":null},{"id":"2605.15877","title":"Shapley Neuron Values for Continual Learning: Which Neurons Matter Most?","created":"2026-05-15","cited_by_count":0,"area":null},{"id":"2609.33725","title":"Reliable Replay through Spatial Coherence in Online Continual Learning","created":"2026-09-27","cited_by_count":0,"area":null}],"next_cursor":null}