Related work

The foundational work on continual learning, 1989 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

15 papers of 5,456Sort Recent · Most cited
  1. 2026
    SafeAdapt: Provably Safe Policy Updates in Deep Reinforcement LearningMaksim Anisimov, Francesco Belardinelli, Matthew WickerarXiv · Imperial College London
    PDF ↗
  2. 2026
    Balanced Online Class-Incremental Learning via Dual ClassifiersShunjie Wen, Thomas Heinis, Dong-Wan ChoiACM/SIGAPP Symposium on Applied Computing · Inha University · Imperial College London
    PDF ↗
  3. 2026
    Functionality Separation: Rethinking Dual-Stream Networks for Class-Incremental LearningQi Gao, Xiaoyan Li, Zhongfan Sun … Wen GaoIEEE TCSVT · Beijing University of Technology · Imperial College London · +1
  4. 2025
    Rapidly Reconfigurable Dynamic Computing in Neural Networks with Fixed Synaptic ConnectivityK. O. Mason, Sonia Sennik, Claudia Clopath … Wilten NicolabioRxiv · University of Calgary · Creative Destruction Lab · +1
  5. 2025
    Improving Deep Optimisation for the Multi-dimensional Knapsack Problem using Elastic Weight ConsolidationAntoine Calame, Ruth Misener, Joshua KnowlesGenetic and Evolutionary Computation Conference Companion · Imperial College London · University of Birmingham
  6. 2025
    Neural signatures of motor memories emerge in neural network modelsJoanna Chang, Claudia Clopath, Juan Álvaro GallegobioRxiv · Imperial College London
  7. 2023
    Explain What You See: Open-Ended Segmentation and Recognition of Occluded 3D ObjectsHamed Ayoobi, H. Kasaei, Ming Cao … Bart VerheijICRA · University of Groningen · Imperial College London
    PDF ↗
  8. 2021
    A study on the plasticity of neural networksTudor Berariu, Wojciech Marian Czarnecki, Soham De … Claudia ClopatharXiv · Imperial College London
    PDF ↗
  9. 2020
    Rational LAMOL: A Rationale-based Lifelong Learning FrameworkKasidis Kanwatchara, Thanapapas Horsuwan, Piyawat Lertvittayakumjorn … Peerapon VateekulACL · Chulalongkorn University · Imperial College London
  10. 2020
    Internet of emotional people: Towards continual affective computing cross cultures via audiovisual signalsJing Han, Zixing Zhang, Maja Pantić, Björn W. SchullerFuture Generation Computer Systems · University of Augsburg · Imperial College London
  11. 2020
    OpenLORIS-Object: A Robotic Vision Dataset and Benchmark for Lifelong Deep LearningQi She, Fan Feng, Xinyue Hao … Rosa H. M. ChanICRA · City University of Hong Kong · Tsinghua University · +4
    PDF ↗
  12. 2020
    Continual Reinforcement Learning with Multi-Timescale ReplayChristos Kaplanis, Claudia Clopath, Murray ShanahanarXiv · Imperial College London
    PDF ↗
  13. 2019
    Policy Consolidation for Continual Reinforcement LearningChristos Kaplanis, Murray Shanahan, Claudia ClopathICML · Imperial College London
    PDF ↗
  14. 2018
    Continual Reinforcement Learning with Complex SynapsesChristos Kaplanis, Murray Shanahan, Claudia ClopathICML · Imperial College London
    PDF ↗
  15. 2017
    Overcoming catastrophic forgetting in neural networksJames Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz … Raia HadsellPNAS · Google DeepMind (United Kingdom) · Imperial College London
    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 written 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.