Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

18 papers of 8,653Sort Recent · Most cited
  1. 2025
    Developing Evolving Adaptability in Biological Intelligence: A Novel Biologically-Inspired Continual Learning Model for Video Saliency PredictionDandan Zhu, Kaiwei Zhang, Kun Zhu … Xiaokang YangTPAMI · East China Normal University · Shanghai Artificial Intelligence Laboratory · +3
  2. 2025
    CEM: A Data-Efficient Method for Large Language Models to Continue Evolving From MistakesHaokun Zhao, Jinyi Han, Jie Shi … Fei YuCIKM · Fudan University · East China Normal University · +1
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  3. 2025
    Exploring the Tradeoff Between Diversity and Discrimination for Continuous Category DiscoveryRuobing Jiang, Yang Liu, Haobing Liu … Chunyang WangCIKM · Ocean University of China · East China Normal University
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  4. 2025
    Lark: Low-Rank Updates After Knowledge Localization for Few-Shot Class-Incremental LearningJinxin Shi, Jiabao Zhao, Yifan Yang … Liang HeICCV · East China Normal University · Donghua University
  5. 2025
    Mitigating the Stability–Plasticity Trade-Off in Neural Networks via Shared Extractors in Class-Incremental LearningMingda Dong, Rui Li, Feng LiuApplied Sciences · East China Normal University · China Mobile (China) · +1
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  6. 2025
    C2BA: Cross-Domain Consistency and Bidirectional Alignment for Cross-Modal Domain-Incremental LearningWeiyi Huang, Xidong Xi, Hailing Wang, Guitao CaoIEEE International Conference on Systems, Man, and Cybern… · Shanghai Key Laboratory of Trustworthy Computing · East China Normal University
  7. 2025
    Rethinking the Stability-Plasticity Dilemma of Dynamically Expandable NetworksMingda Dong, Rui LiSymmetry · East China Normal University · China Mobile (China)
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  8. 2025
    Domain-Incremental Learning Paradigm for scene understanding via Pseudo-Replay GenerationZhifeng Xie, Rui Qiu, Qile He … Xin TanGraphical Models · Shanghai University · East China Normal University
  9. 2025
    CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question AnsweringTianyu Huai, Jie Zhou, Xingjiao Wu … Liang HeCVPR · East China Normal University · Shanghai Open University · +1
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  10. 2025
    One-for-More: Continual Diffusion Model for Anomaly DetectionXiaofan Li, Xin Tan, Zhuo Chen … Yuan XieCVPR · East China Normal University · Xiamen University · +2
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  11. 2025
    Bias to Balance: New-Knowledge-Preferred Few-Shot Class-Incremental Learning via Transition CalibrationHongquan Zhang, Zhizhong Zhang, Xin Tan … Yuan XieTNNLS · East China Normal University · Xiamen University
  12. 2025
    MultiSFL: Towards Accurate Split Federated Learning via Multi-Model Aggregation and Knowledge ReplayZeke Xia, Ming Hu, Dengke Yan … Mingsong ChenAAAI · East China Normal University · Singapore Management University · +1
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  13. 2025
    Interweaving Memories of a Siamese Large Language ModelXin Song, Zhenwei Xue, Guoxiu He … Wei LuAAAI · East China Normal University · Worcester Polytechnic Institute · +1
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  14. 2025
    Efficient Prototypical Classifier for Class-Incremental LearningWei Zhang, Jingyang Qiao, Yuan Xie … Xin TanICASSP · East China Normal University
  15. 2025
    Fresh-CL: Feature Realignment through Experts on Hypersphere in Continual LearningZhongyi Zhou, Yaxin Peng, Pengxing Yi … Chaomin ShenICASSP · East China Normal University · Shanghai University
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  16. 2025
    Prototype Alignment with LoRA Fusion for Class-Incremental LearningWei Zhang, Yuan Xie, Zhizhong Zhang, Xin TanICASSP · East China Normal University
  17. 2025
    Sparse personalized federated class-incremental learningYouchao Liu, Dingjiang HuangInformation Sciences · East China Normal University
  18. 2025
    Spatio-Temporal Prediction on Streaming Data: A Unified Federated Continuous Learning FrameworkHao Miao, Yan Zhao, Chenjuan Guo … Christian S. JensenTKDE · Aalborg University · East China Normal University
About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.