Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

26 papers of 11,817Sort Recent · Most cited
  1. 2025
  2. 2025
  3. 2025
  4. 2025
    Enhancing few-shot class-incremental learning through prototype optimizationMengjuan Jiang, Jiaqing Fan, Fanzhang LiApplied Intelligence
  5. 2025
    Enhancing knowledge retention for continual learning with domain-specific adapters and features gatingO. Hadjerci, Mohamed Abbas Hedjazi, Antoine Letienne, Adel HafianeApplied Intelligence
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  6. 2025
    DCSR: A deep continual learning-based scheme for image super resolution using knowledge distillationAlireza Esmaeilzehi, Hossein Zaredar, M. O. AhmadApplied Intelligence
  7. 2025
    Dual attention-guided distillation for class incremental semantic segmentationPengju Xu, Yan Wang, Bingye Wang, Haiying ZhaoApplied Intelligence
  8. 2025
    Continual learning with selective netsHai Tung Luu, Marton SzemenyeiApplied Intelligence
  9. 2025
  10. 2025
  11. 2024
    Multi-strategy continual learning for knowledge refinement and consolidationXianhua Zeng, Xueyun Nie, La-Quan Li, Ming-Kun ZhouApplied Intelligence
  12. 2024PDF ↗
  13. 2024
    Class-incremental learning via prototype similarity replay and similarity-adjusted regularizationRunji Chen, Guangzhu Chen, Xiaojuan Liao, Wenjie XiongApplied Intelligence
  14. 2024
    Uncertainty-aware enhanced dark experience replay for continual learningQiang Wang, Zhong Ji, Yanwei Pang, Zhongfei ZhangApplied Intelligence
  15. 2024
    A rehearsal framework for computational efficiency in online continual learningCharalampos Davalas, Dimitrios Michail, Christos Diou … Konstantinos TserpesApplied Intelligence
  16. 2023
    Continual learning in an easy-to-hard mannerYifan Chang, Yu-Lu Chen, Ya-Dan Zhang, Wenbo LiApplied Intelligence
  17. 2022
    Continual prune-and-select: class-incremental learning with specialized subnetworksAleksandr Dekhovich, David M. J. Tax, Marcel H. F. Sluiter, Miguel A. BessaApplied Intelligence · Delft University of Technology · Brown University
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  18. 2022
    A robust and anti-forgettiable model for class-incremental learningJianting Chen, Yang XiangApplied Intelligence · Tongji University
  19. 2021
    Reminding the incremental language model via data-free self-distillationHan Wang, Ruiliu Fu, Chengzhang Li … Qingwei ZhaoApplied Intelligence · Chinese Academy of Sciences · Institute of Acoustics · +1
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  20. 2022
    RT-Net: replay-and-transfer network for class incremental object detectionBo Cui, Guyue Hu, Shan YuApplied Intelligence · Chinese Academy of Sciences · Beijing Academy of Artificial Intelligence · +4
  21. 2022
    Continual learning via region-aware memoryKai Zhao, Zhenyong Fu, Jian YangApplied Intelligence · Nanjing University of Science and Technology
  22. 2022
    Learning a dual-branch classifier for class incremental learningLei Guo, Gang Xie, Youyang Qu … Lei CuiApplied Intelligence · Taiyuan University of Technology · Taiyuan University of Science and Technology · +1
  23. 2022
    A multiobjective prediction model with incremental learning ability by developing a multi-source filter neural network for the electrolytic aluminium processLizhong Yao, Wei Ding, Tiantian He … Ling NieApplied Intelligence · Chongqing Normal University · Chongqing University of Science and Technology · +3
  24. 2022
    Self-updating continual learning classification method based on artificial immune systemXin Sun, Haotian Wang, Shulin Liu … Haihua XiaoApplied Intelligence · Shanghai University · Changzhou University
  25. 2020
    SLER: Self-generated long-term experience replay for continual reinforcement learningChunmao Li, Li Yang, Yin-Liang ZHAO … Xupeng GengApplied Intelligence
  26. 2017
    Scalable aggregation predictive analyticsChristos Anagnostopoulos, Fotis Savva, Peter TriantafillouApplied Intelligence · University of Glasgow
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.