{"total":23,"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":"2110.11526","title":"Wide Neural Networks Forget Less Catastrophically","created":"2021-10-21","cited_by_count":64,"area":null},{"id":"2110.00175","title":"DualNet: Continual Learning, Fast and Slow","created":"2021-10-01","cited_by_count":39,"area":null},{"id":"2310.16226","title":"TiC-CLIP: Continual Training of CLIP Models","created":"2023-10-24","cited_by_count":38,"area":null},{"id":"2207.12061","title":"Balancing Stability and Plasticity through Advanced Null Space in Continual Learning","created":"2022-07-25","cited_by_count":30,"area":null},{"id":"2207.05952","title":"Implicit regularization of dropout","created":"2022-07-13","cited_by_count":25,"area":null},{"id":"2203.06514","title":"Sparsity and Heterogeneous Dropout for Continual Learning in the Null Space of Neural Activations","created":"2022-03-12","cited_by_count":19,"area":null},{"id":"2211.03186","title":"Momentum-based Weight Interpolation of Strong Zero-Shot Models for Continual Learning","created":"2022-11-06","cited_by_count":19,"area":null},{"id":"2202.09826","title":"Continual Learning Beyond a Single Model","created":"2022-02-20","cited_by_count":18,"area":null},{"id":"2106.12772","title":"Task-agnostic Continual Learning with Hybrid Probabilistic Models","created":"2021-06-24","cited_by_count":16,"area":null},{"id":"2304.00933","title":"Knowledge Accumulation in Continually Learned Representations and the Issue of Feature Forgetting","created":"2023-04-03","cited_by_count":16,"area":null},{"id":"2504.02107","title":"TiC-LM: A Web-Scale Benchmark for Time-Continual LLM Pretraining","created":"2025-04-02","cited_by_count":15,"area":null},{"id":"2407.10315","title":"Order parameters and phase transitions of continual learning in deep neural networks","created":"2024-07-14","cited_by_count":14,"area":null},{"id":"2103.13511","title":"Addressing catastrophic forgetting for medical domain expansion","created":"2021-03-24","cited_by_count":12,"area":null},{"id":"2305.18444","title":"Continual Task Allocation in Meta-Policy Network via Sparse Prompting","created":"2023-05-29","cited_by_count":11,"area":null},{"id":"2310.01365","title":"Elephant Neural Networks: Born to Be a Continual Learner","created":"2023-10-02","cited_by_count":10,"area":null},{"id":"2503.01595","title":"STAR: Stability-Inducing Weight Perturbation for Continual Learning","created":"2025-03-03","cited_by_count":8,"area":null},{"id":"2203.01012","title":"Continual Feature Selection: Spurious Features in Continual Learning","created":"2022-03-02","cited_by_count":7,"area":null},{"id":"2310.07996","title":"Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer Learning","created":"2023-10-12","cited_by_count":6,"area":null},{"id":"2502.01342","title":"Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss","created":"2025-02-03","cited_by_count":6,"area":null},{"id":"2602.02568","title":"Mitigating Task-Order Sensitivity and Forgetting via Hierarchical Second-Order Consolidation","created":"2026-01-31","cited_by_count":1,"area":null},{"id":"2202.06781","title":"Design of Explainability Module with Experts in the Loop for Visualization and Dynamic Adjustment of Continual Learning","created":"2022-02-14","cited_by_count":0,"area":null},{"id":"2209.02370","title":"Continual Learning, Fast and Slow","created":"2022-09-06","cited_by_count":0,"area":null}],"next_cursor":null}