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. 2025
    Can Synthetic Images Conquer Forgetting? Beyond Unexplored Doubts in Few-Shot Class-Incremental LearningJunsu Kim, Yunhoe Ku, Seungryul BaekICCV · Ulsan National Institute of Science and Technology · MemBrain (Czechia)
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  2. 2025PDF ↗
  3. 2024
    VLM-PL: Advanced Pseudo Labeling approach for Class Incremental Object Detection via Vision-Language ModelJunsu Kim, Yunhoe Ku, Jihyeon Kim … Seungryul BaekCVPR · Ulsan National Institute of Science and Technology
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  4. 2024
    SDDGR: Stable Diffusion-Based Deep Generative Replay for Class Incremental Object DetectionJunsu Kim, Hoseong Cho, Jihyeon Kim … Seungryul BaekCVPR · Ulsan National Institute of Science and Technology
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  5. 2023
    Class-Wise Buffer Management for Incremental Object Detection: An Effective Buffer Training StrategyJunsu Kim, Sumin Hong, Chanwoo Kim … Seungryul BaekICASSP · Ulsan National Institute of Science and Technology · Seoul National University of Science and Technology · +3
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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.