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. 2024
    Information Retrieval Optimization for Non-Exemplar Class Incremental LearningShuai Guo, Yang Gu, Yuan Ma … Yiqiang ChenCIKM · Institute of Computing Technology · University of Chinese Academy of Sciences · +2
  2. 2024
    Continual Learning of Image Classes With Language Guidance From a Vision-Language ModelWentao Zhang, Yujun Huang, Weizhuo Zhang … Ruixuan WangIEEE TCSVT · Sun Yat-sen University · Peng Cheng Laboratory · +1
  3. 2024
    Solving the Catastrophic Forgetting Problem in Generalized Category DiscoveryXinzi Cao, Xiawu Zheng, Guanhong Wang … Yonghong TianCVPR · Sun Yat-sen University · Peng Cheng Laboratory · +2
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  4. 2024
    Adaptive Discovering and Merging for Incremental Novel Class DiscoveryGuangyao Chen, Peixi Peng, Yangru Huang … Yonghong TianAAAI · Peking University · Peng Cheng Laboratory
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  5. 2024
    INCPrompt: Task-Aware Incremental Prompting for Rehearsal-Free Class-Incremental LearningZhiyuan Wang, Xiaoyang Qu, Jing Xiao … Jianzong WangICASSP · Tsinghua–Berkeley Shenzhen Institute · Shenzhen Technology University · +3
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  6. 2024
    KC-Prompt: End-To-End Knowledge-Complementary Prompting for Rehearsal-Free Continual LearningYaowei Li, Yating Liu, Xuxin Cheng … Zhiqi HuangICASSP · Peking University · Peng Cheng Laboratory · +2
  7. 2024
    P2DT: Mitigating Forgetting in Task-Incremental Learning with Progressive Prompt Decision TransformerZhiyuan Wang, Xiaoyang Qu, Jing Xiao … Jianzong WangICASSP · Tsinghua–Berkeley Shenzhen Institute · Shenzhen Technology University · +3
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  8. 2024
    Spatiotemporal Orthogonal Projection Capsule Network for Incremental Few-Shot Action RecognitionYangbo Feng, Junyu Gao, Changsheng XuIEEE Trans. Multimedia · Tianjin University of Technology · Chinese Academy of Sciences · +5
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.