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Perturbation-guided mapping of colorectal cancer cell states to causal mechanismsPreprint

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Exploring the Challenges towards Lifelong Fact LearningPreprint

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Safety-Oriented Stability Biases for Continual Learning

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Compression-aware Continual Learning using Singular Value DecompositionPreprint

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Achieving continual learning in deep neural networks through pseudo-rehearsal

Atkinson, C. (2020) · Otago University Research Archive (University of Otago)

Discriminative Representation Loss (DRL): A More Efficient Approach than Gradient Re-Projection in Continual LearningPreprint

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Mitigating Catastrophic Forgetting In Adaptive Class Incremental Extreme Learning Machine Through Neuron Clustering

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Class-incremental Learning with Rectified Feature-Graph PreservationPreprint

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Adaptive Learning without Forgetting via Low-Complexity Convex Networks

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Continual Learning and Forgetting in Deep Learning Models

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Class incremental learning via Multi-hinge distillation

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Naturally Constrained Online Expectation Maximization

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Class Incremental Learning in Deep Neural Networks

Tong, J. (2021) · UWSpace (University of Waterloo)

Learning to recognize objects by adaptive knowledge transfer

Tao, Q. (2021) · DR-NTU (Nanyang Technological University) · doi:10.32657/10356/151507

Towards Continual Entity Learning in Language Models for Conversational AgentsPreprint

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Adaptive Explainable Continual Learning Framework for Regression Problems with Focus on Power ForecastsPreprint

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Weakly Supervised Continual LearningPreprint

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Kronecker Factorization for Preventing Catastrophic Forgetting in Large-scale Medical Entity LinkingPreprint

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Toward durable representations for continual learning

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Future Research Directions

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Continual Learning with Quasi-Newton MethodsPreprint

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Continual Learning with Score Pseudo Label for Instance SegmentationPreprint

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Semantic drift prediction for class incremental deep metric learning

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Towards Building a Distributed Virtual Flow Meter via Compressed Continual Learning

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Preserve Knowledge with Auxiliary Feature Extractor for Class Incremental Learning

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Towards robust visual recognition: learning from imperfect data

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Fleet learning-based fault detection and diagnosis in the open world

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Does Catastrophic Forgetting Negatively Affect Financial Predictions?

Zurli, A., Bertugli, A., & Credi, J. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-25599-1_37

CLUE: Consolidating Learned and Undergoing Experience in Domain-Incremental Classification

Cai, C., Liu, J., Yu, W., & Guo, Y. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-26348-4_17

Continual lifelong learning in neural systems

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Learning with Adaptive Knowledge for Continual Image-Text Modeling

Luo, Y., Gao, Y., & Lu, Z. (2023) · International Conference on Multimedia Retrieval · doi:10.1145/3591106.3592297

Rehearmixup: Improving Rehearsal-Based Continual LearningPreprint

Zhang, Y., Wu, G., & Yin, Y. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4485798

Continual Learning for Classification Tasks

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Online Continual Learning for Control of Mobile Robots

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Parallel Gradient Blend for Class Incremental Learning

Zhao, Y., Deng, X., Pei, X., Chen, X., & Li, D. (2023) · Proceedings - International Conference on Image Processing · doi:10.1109/icip49359.2023.10222727

Feature Space Augmentation and Old Class Space Preservation for Class Incremental Learning

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A Continual Learning Method for Reducing Class Interference Based on Replay

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Evaluation of Continual Learning Methods for Object Hardness Recognition

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Incremental Land Cover Classification via Strategies for Edge Removal and Feature Point Aggregation

Wang, Z., Ren, B., Hou, B., & Gu, Y. (2023) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss52108.2023.10281966

Deep transfer learning on continual learning

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Effective and efficient continual learning

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QvQ-IL: quantity versus quality in incremental learning

Han, J., Zhang, T., Liu, Z., & Li, Y. (2023) · Neural Computing and Applications · doi:10.1007/s00521-023-09129-0

Consistency is Key: On Data-Efficient Modality Transfer in Speech Translation

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Online Class-Incremental Learning in Image Classification Based on Attention

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Rotation Augmented Distillation for Exemplar-Free Class Incremental Learning with Detailed Analysis

Chen, X., & Chang, X. (2023) · Lecture notes in computer science · doi:10.1007/978-981-99-8462-6_3

Big data and artificial intelligence in ophthalmology - clinical application and future exploration

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Entropy-Guided Self-regulated Learning Without Forgetting for Distribution-Shift Continual Learning with Blurred Task Boundaries

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Exemplar-Free Continual Learning in Vision Transformers via Feature Attention Distillation

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Class Incremental Learning Method for Hyperspectral Images Based on Real Data Playback Mechanism and Classification Network Optimization

Liu, X., Wang, S., Liu, H., & Li, J. (2024) · Lecture notes in electrical engineering · doi:10.1007/978-981-97-0068-4_20

Self-supervised Contrastive Feature Refinement for Few-Shot Class-Incremental Learning

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Meta Lifelong-Learning With Selective and Task-Aware Adaptation

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Incremental Learning for Cross-User sEMG Gesture Recognition: Overcoming User Forgetting

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Comment on hess-2024-56

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None-Exemplar Class Incremental Learning with Feature Contrast and Expanded Distillation

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Evaluating Knowledge Retention in Continual Learning

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Comment on hess-2024-56

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Two-dimensional hybrid incremental learning (2DHIL) framework for semantic segmentation of skin tissues

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Proceedings of the 2nd International Workshop on Networked AI Systems

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Multi-Task Learning Framework for Molecular Property Predictionusing Continual LearningPreprint

Ranjan, S., SHARMA, R., SINGH, V., & Singh, S. K. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4873060

Reply on CC1

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A Decomposition Framework for Class Incremental Text Classification with Dual Prompt Tuning

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Developing Incremental Learning Models with Prototypes

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Robust Self-Paced Incremental Learning for Multitemporal Remote Sensing Image Classification

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Regularization Continual Learning Based on Bayesian Uncertainty Modeling for P300 Brain-Computer Interface

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Balancing Explanations and Adaptation in Offline Continual Learning Systems Using Active Augmented Reply

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Feature Refinement and Calibration for Continual Visual Search

Su, Q., Chen, X., Gu, J., & Li, B. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-8692-3_32

Knowledge Retention in Incremental Learning using Deep Neural Networks

Kumar, A., & Agarwal, S. (2024) · International Conference on Computing, Communication and Networking Technologies (ICCCNT) · doi:10.1109/icccnt61001.2024.10725188

Class Incremental Learning with Forward Memory

Dai, M., Hu, M., Kong, Y., & Gu, Y. (2024) · IEEE/ACIS International Conference on Computer and Information Science (ICIS) · doi:10.1109/icis61260.2024.10778395

Informative Performance Measures for Continual Reinforcement Learning

Denker, Y., Bagus, B., Krawczyk, A., & Gepperth, A. (2024) · IEEE International Conference on Intelligent Computer Communication and Processing (ICCP) · doi:10.1109/iccp63557.2024.10793039

Leveraging Low Rank Filters for Efficient and Knowledge-Preserving Lifelong Learning

Tayyab, M., & Mahalanobis, A. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-74640-6_17

Generative Replay and Multi-steps Knowledge Distillation in Class-Incremental Learning

Meng, Y., Ping, J., Shi, J., & Zhi, R. (2024) · International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP) · doi:10.1145/3707292.3707382

Genetic Algorithm-Guided Diverse Sample Selection with Diffusion-Based Generative Memory for Continual Learning of AcousticsPreprint

Lee, H.-J., & Buu, S.-J. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5133830

Online Continual Learning Based Real-Time Dynamic Digital Twin Model in Industrial Systems

Jia, Z., Tian, C., Ma, X., Peng, B., & Ma, X. (2024) · China Automation Congress (CAC) · doi:10.1109/cac63892.2024.10865734

An Attention-Based Representation Distillation Baseline for Multi-label Continual Learning

Menabue, M., Frascaroli, E., Boschini, M., Bonicelli, L., Porrello, A., & Calderara, S. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-82481-4_15

A rehearsal-based domain-incremental learning method for weld seam tracking robot to enhance generalization

Yan, Y., & Zou, Y. (2025) · Industrial Robot the international journal of robotics research and application · doi:10.1108/ir-11-2024-0528

Multi-Layer Knowledge Distillation for Continual Semantic Segmentation

Wang, Y., Xu, P., Wang, B., & Zhao, H. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10890804

kNN-CL: Enhancing Continual Learning with Nearest Neighbor Retrieval

Wang, E., Li, Q., Chen, H., Sun, R., & Zhou, X. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10889711

Multi-Prototype Grouping for Continual Learning in Visual Question Answering

Zhang, L., Mao, Z., Peng, Y., Fu, Z., & Zhang, Y. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10890400

GIST: Guided Interpretable Large Language Model Strategy Transfer for Multi-Task Reinforcement Learning

Zhao, B., & Tang, Z. (2025) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49660.2025.10890371 · Cited by 1

An Algorithm for Computing Longitudinal Available Overload of Aircraft Based on Intelligent Online Correction of Aerodynamic Parameters

Shan, S., Cheng, Y., Lin, X., & Xu, C. (2024) · IEEE International Conference on Control Theory and Applications (ICoCTA) · doi:10.1109/icocta64736.2024.00058

Lifelong Graph Learning for Graph Summarization

Frank, J., Hoffmann, M., Lell, N., Richerby, D., & Scherp, A. (2024) · IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) · doi:10.1109/wi-iat62293.2024.00036

Improved Incremental Learning for Classification using Weight Space Rotation

Mohanapriya, S., Ram Akaashu, B., Sabarish, V., Mohana Saranya, S., & Dinesh, K. (2025) · International Conference on Emerging Smart Computing and Informatics (ESCI) · doi:10.1109/esci63694.2025.10987962

Improving Efficiency of Unsupervised Skill Discovery by Model Resetting Curriculum

Cao, Y., Liu, Y., Wang, R., Sheng, Q. Z., & Yao, L. (2025) · Communications in computer and information science · doi:10.1007/978-981-96-6954-7_1

ADAPTIVE SIMILARITY-DRIVEN APPROACHES FOR CONTINUAL LEARNING: BRIDGING TASK-AWARE AND TASK-FREE PARADIGMS

Nouri, F., & Nouri, M. (2025) · International Journal of Advanced Artificial Intelligence Research · doi:10.55640/ijaair-v02i01-01

Lifelong Evolution of Swarms

Leuzzi, L., Bacciu, D., Hauert, S., Jones, S., & Cossu, A. (2025) · Genetic and Evolutionary Computation Conference (GECCO) · doi:10.1145/3712256.3726384

Multiple semantic prompt for rehearsal-free continual learning

Chen, J., Zhang, Z., Li, D., & Zeng, Z. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.107860

Class Incremental Learning via Feature Knowledge Prompts

Ma, J., Fan, C., Shi, L., Wang, K., & Kang, Q. (2025) · Wireless and Optical Communications Conference · doi:10.1109/wocc63563.2025.11082253

NeuroDream: A Sleep-Inspired Memory Consolidation Framework for Artificial Neural NetworksPreprint

Tutuncuoglu, B. T. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5377250

Memory-Free Incremental Learning on Pretrained Diffusion Model

Zhang, H., & Liu, J. (2025) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc65474.2025.11090926

Federated Continual Learning for Monocular Depth Estimation in Dynamic Indoor Environments

Farcas, A.-J., Song, H. J., & Mărculescu, R. (2025) · International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) · doi:10.1109/dcoss-iot65416.2025.00026

Real-Time Balancing of Stability and Plasticity in Continual Learning Enables Adaptive Speed Estimation for Lower-Limb Prostheses

Johnson, C. B., Maldonado-Contreras, J. Y., Herrin, K. R., & Young, A. J. (2025) · IEEE Transactions on Medical Robotics and Bionics · doi:10.1109/tmrb.2025.3597014

A Continual Learning Process to Detect Both Previously Learned and Newly Emerging Attack

Park, H., Kim, T., Lee, H., Shin, D., Shin, D., & Park, M. (2025) · Applied Sciences · doi:10.3390/app151810034

A Bio-realistic Synthetic Hippocampus for Robotic Cognition

Vallverdú, J., Feinstein, X., Robertson, P., Kipelkin, I., & Talanov, M. O. (2025) · BioNanoScience · doi:10.1007/s12668-025-02229-2

Attention-Based Mask Network Model for Multirate Sampling Data Fault Diagnosis

Huang, K., Liu, Z., Wu, S., Yang, C., & Gui, W. (2025) · IEEE Transactions on Reliability · doi:10.1109/tr.2025.3616975

Generate Aligned Anomaly: Region-Guided Few-Shot Anomaly Image-Mask Pair Synthesis for Industrial Inspection

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Retaining Temporal Semantics and Relation Topologies for Continual Weakly-Supervised Audio-Visual Video Parsing

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Dark Experience for General Continual Learning: a Strong, Simple Baseline

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Incremental Learning with Maximum Entropy Regularization: Rethinking Forgetting and IntransigencePreprint

Kim, D., Bae, J.-H., Jo, Y., & Choi, J. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.00829 · Cited by 23

A Method for Reducing the Forgetfulness of incremental Learning.

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Mitigating catastrophic forgetting in incremental learning

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Essentials for Class Incremental Learning

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Learning Without Memorizing

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