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. 2025
    Flashbacks to Harmonize Stability and Plasticity in Continual LearningLeila Mahmoodi, Peyman Moghadam, Munawar Hayat … Mehrtash HarandiNeural Networks · Monash University · Commonwealth Scientific and Industrial Research Organisation · +3
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  2. 2025
    Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental LearningJuntae Lee, Munawar Hayat, Sungrack YunCVPR · Qualcomm (United Kingdom)
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  3. 2023
    Geometry and Uncertainty-Aware 3D Point Cloud Class-Incremental Semantic SegmentationYuwei Yang, Munawar Hayat, Jin Zhao … Yinjie LeiCVPR · Sichuan University · Australian Regenerative Medicine Institute · +1
  4. 2022
    CLIP model is an Efficient Continual LearnerVishal Thengane, Salman Khan, Munawar Hayat, Fahad Shahbaz KhanarXiv
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  5. 2020
    iTAML: An Incremental Task-Agnostic Meta-learning ApproachJathushan Rajasegaran, Salman Khan, Munawar Hayat … Mubarak ShahCVPR · Inception Institute of Artificial Intelligence · Linköping University · +1
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  6. 2019
    Random Path Selection for Continual LearningJathushan Rajasegaran, Munawar Hayat, Salman Hameed Khan … Ling ShaoNeurIPS
  7. 2019
    Random Path Selection for Incremental LearningJathushan Rajasegaran, Munawar Hayat, Salman Hameed Khan … Ling ShaoNeurIPS
  8. 2019
    An Adaptive Random Path Selection Approach for Incremental Learning.Jathushan Rajasegaran, Munawar Hayat, Salman Khan … Ming–Hsuan YangNeurIPS
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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. 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.