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.

5 papers of 6,984Sort Recent · Most cited
  1. 2025
    Online Continual Learning via Dynamic Expandable Recursive ModelFei Ye, Adrian G. BorşACM International Conference on Multimedia · University of Electronic Science and Technology of China · Chengdu University of Information Technology · +1
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  2. 2024
    TS-ILM:Class Incremental Learning for Online Action DetectionXiaochen Li, Jian Cheng, Ziying Xia … Nyima TashiACM International Conference on Multimedia · University of Electronic Science and Technology of China · Tibet University
  3. 2022
    Incremental Few-Shot Semantic Segmentation via Embedding Adaptive-Update and Hyper-class RepresentationGuangchen Shi, Yirui Wu, Jun Liu … Tong LüACM International Conference on Multimedia · Hohai University · Singapore University of Technology and Design · +3
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  4. 2022
    Class Gradient Projection For Continual LearningCheng Chen, Ji Zhang, Jingkuan Song, Lianli GaoACM International Conference on Multimedia · University of Electronic Science and Technology of China · Peng Cheng Laboratory
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  5. 2021
    Remember and Reuse: Cross-Task Blind Image Quality Assessment via Relevance-aware Incremental LearningRui Ma, Hanxiao Luo, Qingbo Wu … Linfeng XuACM International Conference on Multimedia · University of Electronic Science and Technology of China
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.