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.

17 papers of 8,653Sort Recent · Most cited
  1. 2026
    Cross Task Knowledge Transfer for Rehearsal-Free Continual LearningShuai Chen, Leike An, Jiaxi Wang … Jibin WangICASSP · China Mobile (China) · Beijing Institute of Technology
  2. 2026
    Few-shot class-incremental learning based on prompt guidance and multimodal fusionHaoming Fang, Haonan Cai, Keming Mao … Xinlu XiaoKnowledge-Based Systems · Northeastern University · China Mobile (China)
  3. 2026
    PS-SNN: pattern separation learning for expandable spiking neural networks in class-incremental learningKe Hu, Liangsheng Wen, Tingting Zhang, Hao ZhangScientific Reports · China Mobile (China)
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  4. 2026
    Learning dynamic representations via an optimally-weighted maximum mean discrepancy optimization framework for continual learningKaihui Huang, Runqing Wu, Jinhui Shen … Fei YeKnowledge-Based Systems · University of Electronic Science and Technology of China · Huazhong University of Science and Technology · +2
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  5. 2026
    Soft Orthogonal Low-Rank Adaptation for Knowledge Sharing in Large Language Model Continual LearningYitong Wang, Xue Han, Wenchun Gao … Junlan FengACL · Jiuquan Iron & Steel (China) · China Mobile (China) · +1
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  6. 2025
    OCCA-SNN: Online Class-Center Anchoring with Alignment for Spiking Neural Networks in Class-Incremental LearningKe Hu, Liangsheng Wen, Tingting Zhang … Hao ZhangInternational Conference on Cognitive and Intelligent Tec… · China Mobile (China)
  7. 2025
    An Incremental Learning Method Based on Uncertainty CalibrationLili Liu, Bo Peng, Shen Wang … Junjie MuJournal of Physics Conference Series · China Mobile (China)
  8. 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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  9. 2025
    Rethinking the Stability-Plasticity Dilemma of Dynamically Expandable NetworksMingda Dong, Rui LiSymmetry · East China Normal University · China Mobile (China)
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  10. 2025
    Selective Parameter Tuning in Large Language Models for Task Specific AdaptationWeijie Wan, Jiangjiang ZhaoIJCNN · South China Normal University · China Mobile (China)
  11. 2025
    Few-Shot Incremental Learning With Context-Aware Spatial Enhancement for Image RecognitionHeng Wu, Ze Yang, Zijun Zheng … Wansong WangIEEE Access · Hangzhou Vocational and Technical College · China Mobile (China) · +4
  12. 2024
    A Knowledge Distillation Method Based on Evidence Theory to Prevent Catastrophic ForgettingBo Peng, Feng Jang, Shen Wang … Min JiaJournal of Physics Conference Series · China Mobile (China)
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  13. 2023
    Prompt Pool Based Class-Incremental Continual Learning for Dialog State TrackingHong Liu, Yucheng Cai, Yuan Zhou … Junlan FengIEEE Automatic Speech Recognition and Understanding Works… · China Mobile (China) · Tsinghua University
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  14. 2023
    Incremental Object Detection based on YOLO v5 and EWC ModelsZeyuan Li, Xinyan Liu, Cheng Zhang … Wei DengInternational Conference on Artificial Intelligence and P… · China Mobile (China) · Southwestern University of Finance and Economics · +1
  15. 2022
    Automatic Model Adaption Method based on Few-Shot Incremental Learning for $\text{IoT}$ ApplicationsDequn Kong, Xiaotao Li, Wai ChenIEEE/CIC International Conference on Communications in Ch… · China Mobile (China)
  16. 2021
    An Incremental Learning Model for Mobile Robot: From Short-Term Memory to Long-Term MemoryDongshu Wang, Kai Yang, Lei Liu, Heshan WangIEEE TAI · Zhengzhou University · China Mobile (China) · +1
  17. 2019
    Incremental Learning from Scratch for Task-Oriented Dialogue SystemsWeikang Wang, Jiajun Zhang, Qian Li … Zhifei LiACL · Shandong Institute of Automation · Institute of Automation · +3
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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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.