{"total":58,"rows":[{"id":"2401.16386","title":"Continual Learning with Pre-Trained Models: A Survey","created":"2024-01-29","cited_by_count":154,"area":null},{"id":"2403.12030","title":"Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning","created":"2024-03-18","cited_by_count":117,"area":null},{"id":"2403.18886","title":"Self-Expansion of Pre-trained Models with Mixture of Adapters for Continual Learning","created":"2024-03-27","cited_by_count":53,"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":"2312.05229","title":"Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration","created":"2023-12-08","cited_by_count":46,"area":null},{"id":"2312.08977","title":"Weighted Ensemble Models Are Strong Continual Learners","created":"2023-12-14","cited_by_count":42,"area":null},{"id":"2412.09441","title":"MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning","created":"2024-12-12","cited_by_count":36,"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":"2505.24816","title":"CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning","created":"2025-05-30","cited_by_count":28,"area":null},{"id":"2408.14471","title":"A Practitioner's Guide to Continual Multimodal Pretraining","created":"2024-08-26","cited_by_count":23,"area":null},{"id":"2403.18383","title":"Generative Multi-modal Models are Good Class-Incremental Learners","created":"2024-03-27","cited_by_count":22,"area":null},{"id":"2410.00911","title":"Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning","created":"2024-10-01","cited_by_count":16,"area":null},{"id":"2403.09857","title":"Few-Shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt","created":"2024-03-14","cited_by_count":15,"area":null},{"id":"2507.07100","title":"Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts","created":"2025-07-09","cited_by_count":13,"area":null},{"id":"2508.07307","title":"MCITlib: Multimodal Continual Instruction Tuning Library and Benchmark","created":"2025-08-10","cited_by_count":13,"area":null},{"id":"2403.09066","title":"Hyperparameters in Continual Learning: A Reality Check","created":"2024-03-14","cited_by_count":12,"area":null},{"id":"2403.15751","title":"F-OAL: Forward-only Online Analytic Learning with Fast Training and Low Memory Footprint in Class Incremental Learning","created":"2024-03-23","cited_by_count":12,"area":null},{"id":"2402.08823","title":"Random Representations Outperform Online Continually Learned Representations","created":"2024-02-13","cited_by_count":11,"area":null},{"id":"2510.16877","title":"Fly-CL: A Fly-Inspired Framework for Enhancing Efficient Decorrelation and Reduced Training Time in Pre-trained Model-based Continual Representation Learning","created":"2025-10-19","cited_by_count":11,"area":null},{"id":"2404.06622","title":"Calibrating Higher-Order Statistics for Few-Shot Class-Incremental Learning with Pre-trained Vision Transformers","created":"2024-04-09","cited_by_count":9,"area":null},{"id":"2501.01045","title":"ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think","created":"2025-01-02","cited_by_count":9,"area":null},{"id":"2410.00645","title":"LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning","created":"2024-10-01","cited_by_count":8,"area":null},{"id":"2502.20032","title":"Order-Robust Class Incremental Learning: Graph-Driven Dynamic Similarity Grouping","created":"2025-02-27","cited_by_count":7,"area":null},{"id":"2601.20852","title":"C3Box: A CLIP-based Class-Incremental Learning Toolbox","created":"2026-01-28","cited_by_count":3,"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":"2403.11537","title":"Semantic Prompting with Image-Token for Continual Learning","created":"2024-03-18","cited_by_count":2,"area":null},{"id":"2404.12407","title":"TV100: A TV Series Dataset that Pre-Trained CLIP Has Not Seen","created":"2024-04-16","cited_by_count":2,"area":null},{"id":"2411.02813","title":"Sparse Orthogonal Parameters Tuning for Continual Learning","created":"2024-11-05","cited_by_count":2,"area":null},{"id":"2509.22580","title":"The Lie of the Average: How Class Incremental Learning Evaluation Deceives You?","created":"2025-09-26","cited_by_count":2,"area":null},{"id":"2510.16914","title":"Domain Generalizable Continual Learning","created":"2025-10-19","cited_by_count":2,"area":null},{"id":"2410.05820","title":"IncSAR: A Dual Fusion Incremental Learning Framework for SAR Target Recognition","created":"2024-10-08","cited_by_count":1,"area":null},{"id":"2412.10900","title":"PEARL: Input-Agnostic Prompt Enhancement with Negative Feedback Regulation for Class-Incremental Learning","created":"2024-12-14","cited_by_count":1,"area":null},{"id":"2503.18403","title":"Knowledge Graph Enhanced Generative Multi-modal Models for Class-Incremental Learning","created":"2025-03-24","cited_by_count":1,"area":null},{"id":"2509.01533","title":"Forward-Only Continual Learning","created":"2025-09-01","cited_by_count":1,"area":null},{"id":"2510.21019","title":"More Than Memory Savings: Zeroth-Order Optimization Mitigates Forgetting in Continual Learning","created":"2025-10-23","cited_by_count":1,"area":null},{"id":"2603.02280","title":"Temporal Imbalance of Positive and Negative Supervision in Class-Incremental Learning","created":"2026-03-02","cited_by_count":1,"area":null},{"id":"2603.08967","title":"Can You Hear, Localize, and Segment Continually? An Exemplar-Free Continual Learning Benchmark for Audio-Visual Segmentation","created":"2026-03-09","cited_by_count":1,"area":null},{"id":"2603.10237","title":"One Adapter for All: Towards Unified Representation in Step-Imbalanced Class-Incremental Learning","created":"2026-03-10","cited_by_count":1,"area":null},{"id":"2404.07729","title":"Realistic Continual Learning Approach using Pre-trained Models","created":"2024-04-11","cited_by_count":0,"area":null},{"id":"2411.17766","title":"Dual Prototypes for Adaptive Pre-Trained Model in Class-Incremental Learning","created":"2024-11-26","cited_by_count":0,"area":null},{"id":"2502.14762","title":"Unlocking [CLS] Features for Continual Post-Training","created":"2025-02-20","cited_by_count":0,"area":null},{"id":"2502.18762","title":"From Offline to Online Memory-Free and Task-Free Continual Learning via Fine-Grained Hypergradients","created":"2025-02-26","cited_by_count":0,"area":null},{"id":"2506.03956","title":"Adapt before Continual Learning","created":"2025-06-04","cited_by_count":0,"area":null},{"id":"2508.07270","title":"OpenHAIV: A Framework Towards Practical Open-World Learning","created":"2025-08-10","cited_by_count":0,"area":null},{"id":"2601.21341","title":"Dynamical Adapter Fusion: Constructing A Global Adapter for Pre-Trained Model-based Class-Incremental Learning","created":"2026-01-29","cited_by_count":0,"area":null},{"id":"2601.21345","title":"Semantic-Guided Dynamic Sparsification for Pre-Trained Model-based Class-Incremental Learning","created":"2026-01-29","cited_by_count":0,"area":null},{"id":"2602.00144","title":"Scalable Analytic Classifiers with Associative Drift Compensation for Class-Incremental Learning of Vision Transformers","created":"2026-01-29","cited_by_count":0,"area":null},{"id":"2602.00573","title":"When Classes Evolve: A Benchmark and Framework for Stage-Aware Class-Incremental Learning","created":"2026-01-31","cited_by_count":0,"area":null},{"id":"2602.20911","title":"From Isolation to Integration: Building an Adaptive Expert Forest for Pre-Trained Model-based Class-Incremental Learning","created":"2026-02-24","cited_by_count":0,"area":null},{"id":"2603.09888","title":"LCA: Local Classifier Alignment for Continual Learning","created":"2026-03-10","cited_by_count":0,"area":null},{"id":"2603.21170","title":"Pruned Adaptation Modules: A Simple yet Strong Baseline for Continual Foundation Models","created":"2026-03-22","cited_by_count":0,"area":null},{"id":"2604.11091","title":"LDEPrompt: Layer-importance guided Dual Expandable Prompt Pool for Pre-trained Model-based Class-Incremental Learning","created":"2026-04-13","cited_by_count":0,"area":null},{"id":"2605.11710","title":"Unlocking Compositional Generalization in Continual Few-Shot Learning","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2605.29592","title":"Non-Forgetting Knowledge Allocation with Bi-level Competition for Class-Incremental Learning","created":"2026-05-28","cited_by_count":0,"area":null},{"id":"2608.16345","title":"Task-Anchored Representation Shaping for Pre-Trained Model-Based Continual Learning","created":"2026-08-17","cited_by_count":0,"area":null},{"id":"2608.26960","title":"Geo-LoRA: Geometry-Aware Subspace Evolution for Low-Rank Adaptation in Continual Learning","created":"2026-08-27","cited_by_count":0,"area":null},{"id":"2608.31096","title":"One Adapter, Many Tasks: Task-Conditioned Feature Transformations for Continual Learning","created":"2026-08-31","cited_by_count":0,"area":null},{"id":"2609.34503","title":"Distribution-Conditioned Task Routing for Class-Incremental Learning","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}