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.

16 papers of 11,817Sort Recent · Most cited
  1. 2026
    Text-Guided Prototype Replay and Classifier Guidance for Incremental Few-Shot Semantic SegmentationLuofeng Zhang, Shengzhe You, Qian Shao … Fei GaoInternational Conference on Multimedia Retrieval
  2. 2026
    DiffusionOPD: A Unified Perspective of On-Policy Distillation in Diffusion ModelsQuanhao Li, Junqiu Yu, Kaixun Jiang … Zu-Xuan WuarXiv
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  3. 2026
  4. 2025
    Flow-Anchored Consistency ModelsYansong Peng, Kai Zhu, Yu Liu … Feng WuarXiv
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  5. 2025PDF ↗
  6. 2024PDF ↗
  7. 2023
    Lifelong Learning With Cycle Memory NetworksJian Peng, Dingqi Ye, Bo Tang … Haifeng LiTNNLS
  8. 2022
    Model Behavior Preserving for Class-Incremental LearningYu Liu, Xiaopeng Hong, Xiaoyu Tao … Yihong GongTNNLS · Xi'an Jiaotong University
  9. 2022
    Feature Estimations Based Correlation Distillation for Incremental Image RetrievalWei Chen, Yu Liu, Nan Pu … M. LewIEEE Trans. Multimedia
  10. 2021
    Overcome Anterograde Forgetting with Cycled Memory NetworksJian Peng, Dingqi Ye, Bo Tang … Haifeng LiarXiv
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  11. 2021
    Structural Knowledge Organization and Transfer for Class-Incremental LearningYu Liu, Xiaopeng Hong, Xiaoyu Tao … Yihong GongACM MM · Xi'an Jiaotong University
  12. 2021
    Reviewing continual learning from the perspective of human-level intelligenceYifan Chang, Wenbo Li, Jian Peng … Haifeng LiarXiv
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  13. 2021
    Learning by Active Forgetting for Neural NetworksJian Peng, Xian Sun, Min Deng … Haifeng LiarXiv · Central South University
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  14. 2021
    From Superficial to Deep: Language Bias driven Curriculum Learning for Visual Question AnsweringMingrui Lao, Yanming Guo, Yu Liu … Michael S. LewACM International Conference on Multimedia · Leiden University · National University of Defense Technology · +1
  15. 2020
    More Classifiers, Less Forgetting: A Generic Multi-classifier Paradigm for Incremental LearningYu Liu, Sarah Parisot, Greg Slabaugh … Tinne TuytelaarsSpringer LNCS · KU Leuven · Huawei Technologies (China) · +1
  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. 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.