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.

6 papers of 8,653Sort Recent · Most cited
  1. 2024
    AWF: Adaptive Weight Fusion for Enhanced Class Incremental Semantic SegmentationZechao Sun, Shuying Piao, Haolin Jin … Luping ZhouInternational Conference on Digital Image Computing: Tech… · The University of Adelaide · The University of Sydney
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  2. 2025
    Evaluating Forgetting in Pretrained Robotic Policy Networks: A Continual Learning Study with OctoYu Ding, Lingqiao Liu, Peng Wang, Lei WangInternational Conference on Digital Image Computing: Tech… · University of Wollongong · The University of Adelaide · +1
  3. 2025
    CIT: Rethinking Class-incremental Semantic Segmentation with a Class Independent TransformationJinchao Ge, Bowen Zhang, Akide Liu … Yang ZhaoPattern Recognition · The University of Adelaide · Monash University · +1
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  4. 2024
    CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary LearningYukun Li, Guansong Pang, Wei Suo … Peng WangTNNLS · Northwestern Polytechnical University · Singapore Management University · +2
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  5. 2022
    A Unified Object Counting Network With Object Occupation PriorShengqin Jiang, Qing Wang, Fengna Cheng … Qingshan LiuIEEE TCSVT · Nanjing University of Information Science and Technology · Nanjing Forestry University · +3
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  6. 2022
    Learning Bayesian Sparse Networks with Full Experience Replay for Continual LearningQingsen Yan, Dong Gong, Yuhang Liu … Qinfeng ShiCVPR · Australian Centre for Robotic Vision · The University of Adelaide · +1
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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 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.