Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

14 papers of 6,984Sort Recent · Most cited
  1. 2025
    MINGLE: Mixture of Null-Space Gated Low-Rank Experts for Test-Time Continual Model MergingZihuan Qiu, Yidong Xu, Chiyuan He … Hongliang LiNeurIPS · University of Electronic Science and Technology of China · Amazon (Germany) · +1
    PDF ↗
  2. 2024
    Efficient Expansion and Gradient Based Task Inference for Replay Free Incremental LearningSoumya Roy, Vinay Kumar Verma, Deepak GuptaWACV · Amazon (Germany) · Duke University
    PDF ↗
  3. 2021
    Kronecker Factorization for Preventing Catastrophic Forgetting in Large-scale Medical Entity LinkingDenis Jered McInerney, Luyang Kong, Kristjan Arumae … Parminder BhatiaarXiv · Universidad del Noreste · Amazon (Germany)
    PDF ↗
  4. 2021
    SynthASR: Unlocking Synthetic Data for Speech RecognitionAmin Fazel, Wei Yang, Yulan Liu … Jasha DroppoInterspeech · Samsung (South Korea) · Amazon (United States) · +1
    PDF ↗
  5. 2021
    Continual Learning for Named Entity RecognitionNatawut Monaikul, Giuseppe Castellucci, Simone Filice, Oleg RokhlenkoAAAI · University of Illinois Chicago · Amazon (Germany)
  6. 2021
    Improving the Quality Trade-Off for Neural Machine Translation Multi-Domain AdaptationEva Hasler, Tobias Domhan, Jonay Trénous … Felix HieberEMNLP · Amazon (Germany)
  7. 2020
    Optimal Continual Learning has Perfect Memory and is NP-hardJeremias Knoblauch, Hisham Husain, Tom DietheICML · University of Warwick · The Alan Turing Institute · +2
    PDF ↗
  8. 2020
    CALM: Continuous Adaptive Learning for Language ModelingKristjan Arumae, Parminder BhatiaarXiv · Amazon (Germany)
    PDF ↗
  9. 2020
    Continual Universal Object DetectionXialei Liu, Hao Yang, Avinash Ravichandran … Stefano SoattoarXiv · Universitat Autònoma de Barcelona · Amazon (Germany)
    PDF ↗
  10. 2020
    Incremental Meta-Learning via Indirect Discriminant AlignmentQing Liu, Orchid Majumder, Alessandro Achille … Stefano SoattoECCV · Johns Hopkins University · Amazon (Germany)
    PDF ↗
  11. 2020
    An Empirical Investigation towards Efficient Multi-Domain Language Model Pre-trainingKristjan Arumae, Qing Sun, Parminder BhatiaEMNLP · Amazon (United States) · Seattle University · +1
    PDF ↗
  12. 2019
    Facilitating Bayesian Continual Learning by Natural Gradients and Stein GradientsYu Chen, Tom Diethe, Neil D. LawrencearXiv · University of Bristol · Amazon (Germany)
    PDF ↗
  13. 2019
    Continual Learning in PracticeTom Diethe, Tom Borchert, Eno Thereska … Neil D. LawrenceNeurIPS · Amazon (Germany)
    PDF ↗
  14. 2019
    Continuous Learning for Large-scale Personalized Domain ClassificationHan Li, Jihwan Lee, Sidharth Mudgal … Young‐Bum KimNAACL · University of Wisconsin–Madison · Amazon (Germany)
    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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.