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
    Entropy-Guided Self-regulated Learning Without Forgetting for Distribution-Shift Continual Learning with Blurred Task BoundariesRui Yang, Matthieu Grard, Emmanuel Dellandréa, Liming ChenSpringer CCIS · Lyon 1 Université · École Centrale de Lyon · +4
  2. 2024
    Where to Forget: A New Attention Stability Metric for Continual Learning EvaluationHaojie Wang, Qingbo Wu, Hongliang Li, Fanman MengSpringer CCIS · University of Electronic Science and Technology of China
  3. 2022
    Metric Learning with Distillation for Overcoming Catastrophic ForgettingPiaoyao Yu, Juanjuan He, Qilang Min, Qi ZhuSpringer CCIS · Wuhan University of Science and Technology
  4. 2022
    Difficulty-Aware Mixup for Replay-based Continual LearningYu-Kai Ling, Ren Yang, Sheng‐De WangSpringer CCIS · National Taiwan University
  5. 2021
    Continual Learning with Differential PrivacyPradnya Desai, Phung Lai, NhatHai Phan, My T. ThaiSpringer CCIS · New Jersey Institute of Technology · University of Florida
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  6. 2021
    On robustness of generative representations against catastrophic forgettingWojciech Masarczyk, Kamil Rafał Deja, T. P. TrzcinskiSpringer CCIS · Warsaw University of Technology · Jagiellonian University
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  7. 2021
    NASIL: Neural Network Architecture Searching for Incremental Learning in Image ClassificationXianya Fu, Wenrui Li, Qiurui Chen … Rui WangSpringer CCIS · Beihang University · State Key Joint Laboratory of Environment Simulation and Pollution Control
  8. 2010
    A Comparison between Growing and Variably Dense Self Organizing Maps for Incremental Learning in Hubel Weisel Models of Concept RepresentationNeo Choon kiat Daniel, Kiruthika Ramanathan, Luping Shi, Prahlad VadakkepatSpringer CCIS · Agency for Science, Technology and Research · Data Storage Institute · +1
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.