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.

8 papers of 8,653Sort Recent · Most cited
  1. 2026
    GAIN: Global-Atomic INteraction Graph for Few-Shot Class-Incremental LearningFan Lyu, Linglan Zhao, Changli Liu … Liang WangIEEE TCSVT · Chinese Academy of Sciences · Institute of Automation · +6
  2. 2025
    Mitigating Catastrophic Forgetting in Online Continual Learning With Dual-Margin Contrastive ReplayFan Lyu, Gongbo Cheng, Daofeng Liu … Liang WangIEEE TCSVT · Chinese Academy of Sciences · Institute of Automation · +2
  3. 2025
    Class-Specific Knowledge-Guided Multimodal Prompt Tuning for Few-Shot Class-Incremental LearningFangying Xiong, Zhaoquan Yuan, Xiao Wu, Changsheng XuIEEE TCSVT · Southwest Jiaotong University · Chinese Academy of Sciences · +1
  4. 2025
    Few-Shot Class-Incremental Learning via Asymmetric Supervised Contrastive LearningDuo Liu, Linglan Zhao, Zhongqiang Zhang … Liang WangIEEE TCSVT · Shanghai Jiao Tong University · Tencent (China) · +4
  5. 2024
    Class Incremental Learning for Light-Weighted NetworksZhe Tao, Lu Yu, Hantao Yao … Changsheng XuIEEE TCSVT · Tianjin University of Technology · Chinese Academy of Sciences · +2
  6. 2024
    ESDB: Expand the Shrinking Decision Boundary via One-to-Many Information Matching for Continual Learning With Small MemoryKunchi Li, Hongyang Chen, Jun Wan, Shan YuIEEE TCSVT · Chinese Academy of Sciences · Shandong Institute of Automation · +3
  7. 2023
    Contrastive Correlation Preserving Replay for Online Continual LearningDan-Ping Yu, Mingyi Zhang, Mantian Li … Kaiqi HuangIEEE TCSVT · Harbin Institute of Technology · Chinese Academy of Sciences · +4
  8. 2020
    Fast Adapting Without Forgetting for Face RecognitionHao Liu, Xiangyu Zhu, Zhen Lei … Stan Z. LiIEEE TCSVT · Chinese Academy of Sciences · Beijing Academy of Artificial Intelligence · +3
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.