Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

8 papers of 6,984Sort Recent · Most cited
  1. 2026
    Learning a Fix and Explore Framework for Continuous Generalized Category DiscoveryChunming Li, Shidong Wang, Haofeng ZhangAAAI · Nanjing University of Science and Technology · Newcastle University
  2. 2026
    A continual learning framework with long-term and multiple short-term memory networksShangge Liu, Lei Wang, Rui Yan … Yang GaoNeural Networks · Nanjing Tech University · University of Wollongong · +2
  3. 2026
    Boosting Few-Shot Continual Learning via Self-Adaptive EvolutionZiqi Gu, Chunyan Xu, Yue Wang … Zhen CuiTIP · Nanjing University of Science and Technology · Nanyang Technological University · +2
  4. 2026
    InfBA: Interference-Free Bottleneck Adaptation for Continual LearningYan-Shuo Liang, Weiwei LiTPAMI · Nanjing University of Science and Technology
  5. 2026
    Preserving Fairness in Knowledge Transfer for Exemplar-Free Class-Incremental Learning via Semantic PropagationFankang Xu, Lu Jin, Yanpeng Sun, Zechao LiTIP · Nanjing University of Science and Technology · Singapore University of Technology and Design
  6. 2026
    Topology-Evolving Semantic Adaptation for Few-Shot Class-Incremental Action RecognitionXingyu Zhu, Binqian Xu, Jiachao Zhang … Xiangbo ShuIEEE Trans. Multimedia · Nanjing University of Science and Technology · Nanjing Institute of Technology · +1
  7. 2026
    A Theoretical Perspective on Streaming Noisy Data With Distribution ShiftWenshui Luo, Shuo Chen, Tao Zhou, Chen GongTPAMI · Shanghai Jiao Tong University · Nanjing University of Science and Technology
  8. 2026
    Dual prototypes for adaptive pre-trained model in class-incremental learningZhiming Xu, Zhiming Xu, Suorong Yang … Jian ZhaoNeural Networks · Nanjing University · Nanjing University of Science and Technology
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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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.