Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

4 papers of 11,817Sort Recent · Most cited
  1. 2025
    Spatial Modelling with Incremental Learning and Spatio Temporal Matrix: A Study on Urban Growth of Bengaluru, IndiaY. Mittal, Rahisha Thottolil, Uttam KumarIEEE India Geoscience and Remote Sensing Symposium (InGARSS)
  2. 2024
    Caption, Create, Continue: Continual Learning with Pre-trained Generative Vision-Language ModelsIndu Solomon, A. P. P. Aung, Uttam Kumar, Senthilnath JayaveluCIKM
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  3. 2024
    U-TELL: Unsupervised Task Expert Lifelong LearningIndu Solomon, A. P. P. Aung, Uttam Kumar, Senthilnath JayaveluInternational Conference on Information Photonics
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  4. 2021
    SGDOL: Self-evolving Generative and Discriminative Online Learning for Data Stream ClassificationDeeksha Aggarwal, J. Senthilnath, Uttam Kumar … Xiaoli LiICDM · International Institute of Information Technology Bangalore · Agency for Science, Technology and Research · +2
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.