{"total":291,"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":"2211.13218","title":"CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning","created":"2022-11-23","cited_by_count":450,"area":null},{"id":"2405.02246","title":"What matters when building vision-language models?","created":"2024-05-03","cited_by_count":326,"area":"mllm"},{"id":"2207.12819","title":"S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning","created":"2022-07-26","cited_by_count":246,"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":"2403.11549","title":"Boosting Continual Learning of Vision-Language Models via Mixture-of-Experts Adapters","created":"2024-03-18","cited_by_count":199,"area":"mllm"},{"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":"2205.12393","title":"Fine-tuned Language Models are Continual Learners","created":"2022-05-24","cited_by_count":156,"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":"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":"2303.06628","title":"Preventing Zero-Shot Transfer Degradation in Continual Learning of Vision-Language Models","created":"2023-03-12","cited_by_count":112,"area":"mllm"},{"id":"2205.09357","title":"Continual Pre-Training Mitigates Forgetting in Language and Vision","created":"2022-05-19","cited_by_count":83,"area":null},{"id":"2305.19270","title":"Learning without Forgetting for Vision-Language Models","created":"2023-05-30","cited_by_count":79,"area":"mllm"},{"id":"2403.00504","title":"Learning and Leveraging World Models in Visual Representation Learning","created":"2024-03-01","cited_by_count":72,"area":"wm"},{"id":"2210.03114","title":"CLIP model is an Efficient Continual Learner","created":"2022-10-06","cited_by_count":65,"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":"2205.00329","title":"Continual Learning with Foundation Models: An Empirical Study of Latent Replay","created":"2022-04-30","cited_by_count":61,"area":null},{"id":"2302.00903","title":"No One Left Behind: Real-World Federated Class-Incremental Learning","created":"2023-02-02","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":"2309.04430","title":"Create Your World: Lifelong Text-to-Image Diffusion","created":"2023-09-08","cited_by_count":46,"area":"diffusion"},{"id":"2205.05467","title":"A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentials","created":"2022-05-11","cited_by_count":45,"area":null},{"id":"2303.12696","title":"Dense Network Expansion for Class Incremental Learning","created":"2023-03-22","cited_by_count":45,"area":null},{"id":"2211.15969","title":"Isolation and Impartial Aggregation: A Paradigm of Incremental Learning without Interference","created":"2022-11-29","cited_by_count":44,"area":null},{"id":"2203.04640","title":"Memory Efficient Continual Learning with Transformers","created":"2022-03-09","cited_by_count":43,"area":null},{"id":"2308.10445","title":"When Prompt-based Incremental Learning Does Not Meet Strong Pretraining","created":"2023-08-21","cited_by_count":41,"area":null},{"id":"2112.15022","title":"Continually Learning Self-Supervised Representations with Projected Functional Regularization","created":"2021-12-30","cited_by_count":38,"area":null},{"id":"2210.03482","title":"CLAD: A realistic Continual Learning benchmark for Autonomous Driving","created":"2022-10-07","cited_by_count":36,"area":null},{"id":"2305.00316","title":"The Ideal Continual Learner: An Agent That Never Forgets","created":"2023-04-29","cited_by_count":35,"area":null},{"id":"2407.05342","title":"Mind the Interference: Retaining Pre-trained Knowledge in Parameter Efficient Continual Learning of Vision-Language Models","created":"2024-07-07","cited_by_count":34,"area":"mllm"},{"id":"2410.17594","title":"How to Continually Adapt Text-to-Image Diffusion Models for Flexible Customization?","created":"2024-10-23","cited_by_count":33,"area":"diffusion"},{"id":"2307.12427","title":"Augmented Box Replay: Overcoming Foreground Shift for Incremental Object Detection","created":"2023-07-23","cited_by_count":32,"area":null},{"id":"2403.20317","title":"Convolutional Prompting meets Language Models for Continual Learning","created":"2024-03-29","cited_by_count":32,"area":null},{"id":"2407.08536","title":"Exemplar-free Continual Representation Learning via Learnable Drift Compensation","created":"2024-07-11","cited_by_count":31,"area":null},{"id":"2311.17601","title":"Continual Learning with Low Rank Adaptation","created":"2023-11-29","cited_by_count":29,"area":null},{"id":"2403.11530","title":"Continual Forgetting for Pre-trained Vision Models","created":"2024-03-18","cited_by_count":29,"area":null},{"id":"2407.10281","title":"Beyond Prompt Learning: Continual Adapter for Efficient Rehearsal-Free Continual Learning","created":"2024-07-14","cited_by_count":29,"area":null},{"id":"2204.13349","title":"Continual Learning with Bayesian Model based on a Fixed Pre-trained Feature Extractor","created":"2022-04-28","cited_by_count":27,"area":null},{"id":"2308.13305","title":"Dynamic Residual Classifier for Class Incremental Learning","created":"2023-08-25","cited_by_count":26,"area":null},{"id":"2211.13999","title":"CoMFormer: Continual Learning in Semantic and Panoptic Segmentation","created":"2022-11-25","cited_by_count":25,"area":null},{"id":"2305.04769","title":"BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning","created":"2023-05-08","cited_by_count":25,"area":null},{"id":"2306.06289","title":"SegViTv2: Exploring Efficient and Continual Semantic Segmentation with Plain Vision Transformers","created":"2023-06-09","cited_by_count":25,"area":null},{"id":"2308.13324","title":"ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analysis","created":"2023-08-25","cited_by_count":25,"area":null},{"id":"2403.19137","title":"CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models","created":"2024-03-28","cited_by_count":25,"area":"mllm"},{"id":"2303.10725","title":"SIESTA: Efficient Online Continual Learning with Sleep","created":"2023-03-19","cited_by_count":24,"area":null},{"id":"2303.18171","title":"How Efficient Are Today's Continual Learning Algorithms?","created":"2023-03-29","cited_by_count":24,"area":null},{"id":"2312.10549","title":"Catastrophic Forgetting in Deep Learning: A Comprehensive Taxonomy","created":"2023-12-16","cited_by_count":24,"area":null},{"id":"2203.13167","title":"Towards Exemplar-Free Continual Learning in Vision Transformers: an Account of Attention, Functional and Weight Regularization","created":"2022-03-24","cited_by_count":23,"area":null},{"id":"2204.08766","title":"Modeling Missing Annotations for Incremental Learning in Object Detection","created":"2022-04-19","cited_by_count":23,"area":"distill"},{"id":"2506.05453","title":"MLLM-CL: Continual Learning for Multimodal Large Language Models","created":"2025-06-05","cited_by_count":23,"area":"mllm"},{"id":"2303.09447","title":"Steering Prototypes with Prompt-tuning for Rehearsal-free Continual Learning","created":"2023-03-16","cited_by_count":22,"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":"2404.12526","title":"Adaptive Memory Replay for Continual Learning","created":"2024-04-18","cited_by_count":22,"area":null},{"id":"2207.13516","title":"Online Continual Learning with Contrastive Vision Transformer","created":"2022-07-24","cited_by_count":21,"area":null},{"id":"2503.04229","title":"Synthetic Data is an Elegant GIFT for Continual Vision-Language Models","created":"2025-03-06","cited_by_count":21,"area":"mllm"},{"id":"2403.20126","title":"ECLIPSE: Efficient Continual Learning in Panoptic Segmentation with Visual Prompt Tuning","created":"2024-03-29","cited_by_count":20,"area":null},{"id":"2403.08755","title":"DAM: Dynamic Adapter Merging for Continual Video QA Learning","created":"2024-03-13","cited_by_count":19,"area":null},{"id":"2508.08165","title":"Integrating Task-Specific and Universal Adapters for Pre-Trained Model-based Class-Incremental Learning","created":"2025-08-11","cited_by_count":19,"area":null},{"id":"2403.13499","title":"Improved Baselines for Data-efficient Perceptual Augmentation of LLMs","created":"2024-03-20","cited_by_count":18,"area":null},{"id":"2412.18219","title":"Adapter Merging with Centroid Prototype Mapping for Scalable Class-Incremental Learning","created":"2024-12-24","cited_by_count":18,"area":null},{"id":"2503.18985","title":"LoRA Subtraction for Drift-Resistant Space in Exemplar-Free Continual Learning","created":"2025-03-23","cited_by_count":18,"area":null},{"id":"2206.14085","title":"Continual Learning with Transformers for Image Classification","created":"2022-06-28","cited_by_count":17,"area":null},{"id":"2212.05102","title":"A soft nearest-neighbor framework for continual semi-supervised learning","created":"2022-12-09","cited_by_count":17,"area":null},{"id":"2302.07994","title":"\\`A-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable Prompting","created":"2023-02-15","cited_by_count":17,"area":null},{"id":"2303.07223","title":"PromptFusion: Decoupling Stability and Plasticity for Continual Learning","created":"2023-03-13","cited_by_count":17,"area":null},{"id":"2407.11499","title":"Bridge Past and Future: Overcoming Information Asymmetry in Incremental Object Detection","created":"2024-07-16","cited_by_count":16,"area":"distill"},{"id":"2212.14284","title":"Resolving Task Confusion in Dynamic Expansion Architectures for Class Incremental Learning","created":"2022-12-29","cited_by_count":15,"area":null},{"id":"2304.03931","title":"Exploring Data Geometry for Continual Learning","created":"2023-04-08","cited_by_count":15,"area":null},{"id":"2308.03374","title":"Heterogeneous Forgetting Compensation for Class-Incremental Learning","created":"2023-08-07","cited_by_count":15,"area":null},{"id":"2403.10245","title":"CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning","created":"2024-03-15","cited_by_count":15,"area":"mllm"},{"id":"2503.00823","title":"Task-Agnostic Guided Feature Expansion for Class-Incremental Learning","created":"2025-03-02","cited_by_count":15,"area":null},{"id":"2303.06580","title":"Towards General Purpose Medical AI: Continual Learning Medical Foundation Model","created":"2023-03-12","cited_by_count":14,"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":"2310.19272","title":"NPCL: Neural Processes for Uncertainty-Aware Continual Learning","created":"2023-10-30","cited_by_count":14,"area":null},{"id":"2507.07831","title":"Rethinking Query-based Transformer for Continual Image Segmentation","created":"2025-07-10","cited_by_count":14,"area":null},{"id":"2509.16738","title":"Mixture of Noise for Pre-Trained Model-Based Class-Incremental Learning","created":"2025-09-20","cited_by_count":14,"area":null},{"id":"2306.01904","title":"Overcoming the Stability Gap in Continual Learning","created":"2023-06-02","cited_by_count":13,"area":null},{"id":"2403.07292","title":"Continual All-in-One Adverse Weather Removal with Knowledge Replay on a Unified Network Structure","created":"2024-03-12","cited_by_count":13,"area":null},{"id":"2405.11067","title":"Bayesian Learning-driven Prototypical Contrastive Loss for Class-Incremental Learning","created":"2024-05-17","cited_by_count":13,"area":null},{"id":"2508.06202","title":"LoRA in LoRA: Towards Parameter-Efficient Architecture Expansion for Continual Visual Instruction Tuning","created":"2025-08-08","cited_by_count":13,"area":"mllm"},{"id":"2211.14763","title":"Multi-Label Continual Learning using Augmented Graph Convolutional Network","created":"2022-11-27","cited_by_count":12,"area":null},{"id":"2307.16419","title":"Subspace Distillation for Continual Learning","created":"2023-07-31","cited_by_count":12,"area":null},{"id":"2311.17450","title":"Continual Learning for Image Segmentation with Dynamic Query","created":"2023-11-29","cited_by_count":12,"area":null},{"id":"2401.01598","title":"Learning Prompt with Distribution-Based Feature Replay for Few-Shot Class-Incremental Learning","created":"2024-01-03","cited_by_count":12,"area":null},{"id":"2401.17992","title":"Multilinear Operator Networks","created":"2024-01-31","cited_by_count":12,"area":null},{"id":"2410.20178","title":"LLMs Can Evolve Continually on Modality for X-Modal Reasoning","created":"2024-10-26","cited_by_count":12,"area":"lr"},{"id":"2410.20444","title":"Vector Quantization Prompting for Continual Learning","created":"2024-10-27","cited_by_count":12,"area":null},{"id":"2303.14423","title":"Task-Attentive Transformer Architecture for Continual Learning of Vision-and-Language Tasks Using Knowledge Distillation","created":"2023-03-25","cited_by_count":11,"area":"distill"},{"id":"2408.16939","title":"Theoretical Insights into Overparameterized Models in Multi-Task and Replay-Based Continual Learning","created":"2024-08-29","cited_by_count":11,"area":null},{"id":"2410.00064","title":"M2Distill: Multi-Modal Distillation for Lifelong Imitation Learning","created":"2024-09-30","cited_by_count":11,"area":"offlinerl"},{"id":"2503.08510","title":"External Knowledge Injection for CLIP-Based Class-Incremental Learning","created":"2025-03-11","cited_by_count":11,"area":null},{"id":"2503.12745","title":"ProtoDepth: Unsupervised Continual Depth Completion with Prototypes","created":"2025-03-17","cited_by_count":11,"area":null},{"id":"2505.23271","title":"LADA: Scalable Label-Specific CLIP Adapter for Continual Learning","created":"2025-05-29","cited_by_count":11,"area":"mllm"},{"id":"2208.00777","title":"D3Former: Debiased Dual Distilled Transformer for Incremental Learning","created":"2022-07-25","cited_by_count":10,"area":null},{"id":"2308.01698","title":"Balanced Destruction-Reconstruction Dynamics for Memory-replay Class Incremental Learning","created":"2023-08-03","cited_by_count":10,"area":null},{"id":"2308.04749","title":"Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks","created":"2023-08-09","cited_by_count":10,"area":null},{"id":"2308.12510","title":"Masked Autoencoders are Efficient Class Incremental Learners","created":"2023-08-24","cited_by_count":10,"area":null},{"id":"2407.16354","title":"Strike a Balance in Continual Panoptic Segmentation","created":"2024-07-23","cited_by_count":10,"area":null},{"id":"2210.07016","title":"Learning with Style: Continual Semantic Segmentation Across Tasks and Domains","created":"2022-10-13","cited_by_count":9,"area":null},{"id":"2311.01200","title":"Continual Learning Under Language Shift","created":"2023-11-02","cited_by_count":9,"area":null}],"next_cursor":"100"}