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.

4 papers of 8,653Sort Recent · Most cited
  1. 2024
    Disentangled Representations for Continual Learning: Overcoming Forgetting and Facilitating Knowledge TransferZhaopeng Xu, Qi Qin, Bing Liu, Dongyan ZhaoSpringer LNCS · Peking University · University of Illinois Chicago · +1
  2. 2021
    Continual Learning by Using Information of Each Class HolisticallyWenpeng Hu, Qi Qin, Mengyu Wang … Bing LiuAAAI · Peking University
  3. 2021
    BNS: Building Network Structures Dynamically for Continual LearningQi Qin, Han Peng, Wen-Rui Hu … Bing LiuNeurIPS
  4. 2020
    Using the Past Knowledge to Improve Sentiment ClassificationQi Qin, Wenpeng Hu, Bing LiuEMNLP · Peking University · King 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. 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.