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.

3 papers of 8,653Sort Recent · Most cited
  1. 2024
    Remembering Transformer for Continual LearningYuwei Sun, Ippei Fujisawa, Arthur Juliani … Ryota KanaiIJCNN · Konya Eğitim ve Araştırma Hastanesi · Microsoft Research (United Kingdom) · +1
    PDF ↗
  2. 2020
    Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic ForgettingZeke Xie, Fengxiang He, Shaopeng Fu … Masashi SugiyamaNeural Computation · RIKEN Center for Advanced Intelligence Project · The University of Tokyo · +1
    PDF ↗
  3. 2020
    Generalisation Guarantees for Continual Learning with Orthogonal Gradient DescentMehdi Bennani, Thang Doan, Masashi SugiyamaarXiv · École Nationale Supérieure des Mines de Paris · McGill University · +1
    PDF ↗
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.