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.

6 papers of 11,817Sort Recent · Most cited
  1. 2022
    Attractive and repulsive training to address inter-task forgetting issues in continual learningHongjun Choi, Dong-Wan Choi, Dong-Wan ChoiNeurocomputing · Inha University
  2. 2022
    TA-SBERT : Token Attention Sentence-BERT for Improving Sentence RepresentationJaejin Seo, Sangwon Lee, Ling Liu, Wonik ChoiIEEE Access · Inha University · Georgia Institute of Technology
  3. 2021PDF ↗
  4. 2021
    Dynamic Mitigation of Catastrophic Forgetting Using the Sampling NetworkDae Yong Hong, Yan Li, Byeong‐Seok ShinSpringer LNCS · Inha University
  5. 2019
    Hierarchical Open-Set Object Detection in Unseen DataYeong Kim, Dong Kyun Shin, Minhaz Uddin Ahmed, Phill Kyu RheeSymmetry · Inha University
  6. 2019
    Predictive EWC: mitigating catastrophic forgetting of neural network through pre-prediction of learning dataDae-Yong Hong, Yan Li, Byeong‐Seok ShinJournal of Ambient Intelligence and Humanized Computing · Inha University
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.