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.

5 papers of 8,653Sort Recent · Most cited
  1. 2026
    Adaptive Quantization for Stable Knowledge Acquisition in Quantization-Aware Continual LearningDe Cheng, Kun Gu, Lingfeng He … Xinbo GaoIEEE TCSVT · Xidian University · Huawei Technologies (China)
  2. 2025
    Achieving Plasticity-Stability Trade-Off in Continual Learning Through Adaptive Orthogonal ProjectionDe Cheng, Yusong Hu, Nannan Wang … Xinbo GaoIEEE TCSVT · Xidian University · Xi’an University of Posts and Telecommunications · +2
  3. 2025
    Prompt-Based Concept Learning for Few-Shot Class-Incremental LearningShuo Li, Fang Liu, Licheng Jiao … Wenping MaIEEE TCSVT · Ministry of Education of the People's Republic of China · Xidian University
  4. 2024
    Efficient Statistical Sampling Adaptation for Exemplar-Free Class Incremental LearningDe Cheng, Yuxin Zhao, Nannan Wang … Xinbo GaoIEEE TCSVT · Xidian University · Northwestern Polytechnical University · +1
  5. 2021
    Continuous Multi-View Human Action RecognitionQiang Wang, Gan Sun, Jiahua Dong … Zhengming DingIEEE TCSVT · Xidian University · Shenyang University · +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.