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.

13 papers of 11,817Sort Recent · Most cited
  1. 2020
    Simple Lifelong Learning MachinesJoshua T. Vogelstein, Jayanta Dey, Hayden S. Helm … Carey E. PriebeTPAMI · Johns Hopkins University · Baylor College of Medicine · +1
    PDF ↗
  2. 2022
    PROD: Progressive Distillation for Dense RetrievalZhenghao Lin, Yeyun Gong, Xiao Liu … Nan DuanACM Web Conference 2023 · Xiamen University · Microsoft Research Asia (China) · +1
    PDF ↗
  3. 2022
    Continual Learning about Objects in the Wild: An Interactive ApproachDan Bohus, Sean Andrist, Ashley Feniello … Eric Horvitz2022 International Conference on Multimodal Interaction · Microsoft (United States)
  4. 2021
    Continual Neural Network Model RetrainingXiaofeng Zhu, Diego KlabjanIEEE International Conference on Big Data (Big Data) · Microsoft (United States) · Northwestern University
  5. 2020
    K-Adapter: Infusing Knowledge into Pre-Trained Models with AdaptersRuize Wang, Duyu Tang, Nan Duan … Ming ZhouACL · Fudan University · Microsoft (United States) · +1
    PDF ↗
  6. 2021
    Language Scaling for Universal Suggested Replies ModelQianlan Ying, Payal Bajaj, Budhaditya Deb … Daxin JiangNAACL · Microsoft (United States) · Microsoft Research Asia (China) · +3
    PDF ↗
  7. 2020
    Explicit Filterbank Learning for Neural Image Style Transfer and Image ProcessingDongdong Chen, Lu Yuan, Jing Liao … Gang HuaTPAMI · University of Science and Technology of China · Microsoft (United States) · +1
  8. 2019
    AutoML @ NeurIPS 2018 challenge: Design and ResultsHugo Jair Escalante, Wei-Wei Tu, Isabelle Guyon … Qiang YangMachine Learning · Gleason (United States) · National Institute of Astrophysics, Optics and Electronics · +8
    PDF ↗
  9. 2019
    Introduction to the Special Section on Advances in Causal Discovery and InferenceJiuyong Li, Kun Zhang, Emre Kıcıman, Peng CuiACM Transactions · University of South Australia · Carnegie Mellon University · +2
  10. 2018
    An Empirical Study of Example Forgetting during Deep Neural Network LearningMariya Toneva, Alessandro Sordoni, Rémi Tachet des Combes … Geoffrey J. GordonICLR · Carnegie Mellon University · Microsoft (United States) · +1
    PDF ↗
  11. 2018
    Accumulating Conversational Skills Using Continual LearningSung‐Jin LeeIEEE Spoken Language Technology Workshop (SLT) · Microsoft (United States)
  12. 2016
    Differentiable Programs with Neural LibrariesAlexander L. Gaunt, Marc Brockschmidt, Nate Kushman, Daniel TarlowICML · Microsoft (United States)
    PDF ↗
  13. 2007
    Principles of Lifelong Learning for Predictive User ModelingAshish Kapoor, Eric HorvitzSpringer LNCS · Microsoft (United States)
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.