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.

16 papers of 8,653Sort Recent · Most cited
  1. 2026
    Text-Guided Prototype Replay and Classifier Guidance for Incremental Few-Shot Semantic SegmentationLuofeng Zhang, Shengzhe You, Qian Shao … Fei Gao2026 International Conference on Multimedia Retrieval · Zhejiang University of Technology · Zhejiang University
  2. 2025
    TIPS: Two-level prompt selection for more stability-plasticity balance in continual learningZhikun Feng, Liang Peng, Kang Dang … Jionglong SuPattern Recognition · University of Electronic Science and Technology of China · Chengdu University of Information Technology · +3
  3. 2025
    Decoupling Overlapped Feature Spaces: When Continual Learning Meets Fine-Grain ClassificationZhikun Feng, Mingyu Wu, Ping Kuang … Yu LiuIEEE International Conference on Multimedia and Expo (ICME) · University of Electronic Science and Technology of China · Xi’an Jiaotong-Liverpool University
  4. 2024PDF ↗
  5. 2024
    Lifelong Learning With Cycle Memory NetworksJian Peng, Dingqi Ye, Bo Tang … Haifeng LiTNNLS · Shanghai Zhangjiang Laboratory · Tsinghua University · +5
  6. 2022
    Lifelong Fine-Grained Image RetrievalWei Chen, Haoyang Xu, Nan Pu … Michael S. LewIEEE Trans. Multimedia · Xidian University · Leiden University · +2
  7. 2022
    Meta Reconciliation Normalization for Lifelong Person Re-IdentificationNan Pu, Yu Liu, Wei Chen … Michael S. LewACM International Conference on Multimedia · Leiden University · Dalian University of Technology
  8. 2023
    Model Behavior Preserving for Class-Incremental LearningYu Liu, Xiaopeng Hong, Xiaoyu Tao … Yihong GongTNNLS · Xi'an Jiaotong University
  9. 2021
    Overcome Anterograde Forgetting with Cycled Memory NetworksJian Peng, Dingqi Ye, Bo Tang … Haifeng LiarXiv
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  10. 2021
    Structural Knowledge Organization and Transfer for Class-Incremental LearningYu Liu, Xiaopeng Hong, Xiaoyu Tao … Yihong GongACM MM · Xi'an Jiaotong University
  11. 2021
    Reviewing continual learning from the perspective of human-level intelligenceYifan Chang, Wenbo Li, Jian Peng … Haifeng LiarXiv
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  12. 2021
    Learning by Active Forgetting for Neural NetworksJian Peng, Xian Sun, Min Deng … Haifeng LiarXiv · Central South University
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  13. 2021
    Lifelong Person Re-Identification via Adaptive Knowledge AccumulationNan Pu, Wei Chen, Yu Liu … Michael S. LewCVPR · Leiden University · Dalian University of Technology
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  14. 2021
    Feature Estimations Based Correlation Distillation for Incremental Image RetrievalWei Chen, Yu Liu, Nan Pu … Michael S. LewIEEE Trans. Multimedia · Leiden University · Dalian University of Technology · +1
  15. 2020
    More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental LearningYu Liu, Sarah Parisot, Greg Slabaugh … Tinne TuytelaarsECCV · KU Leuven · Huawei Technologies (China) · +1
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  16. 2020
    On the Exploration of Incremental Learning for Fine-grained Image RetrievalWei Chen, Yu Liu, Weiping Wang … Michael S. LewBMVC · Leiden University · KU Leuven · +1
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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.