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.

20 papers of 8,653Sort Recent · Most cited
  1. 2026
    Learning sculpts orthogonal task manifolds for continual skill learning in recurrent networksZihan Liu, Anno C. Kurth, Yuma Osako, Toshitake AsabukibioRxiv · Chinese University of Hong Kong · RIKEN Center for Brain Science · +2
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  2. 2026
    Building Intelligent Agents with Neuro-Symbolic ConceptsJiayuan Mao, Josh Tenenbaum, Jiajun WuCommunications of the ACM · Massachusetts Institute of Technology · Institute of Cognitive and Brain Sciences · +1
  3. 2025
    CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental LearningJiangpeng He, Zhihao Duan, Fengqing ZhuCVPR · Massachusetts Institute of Technology · Purdue University West Lafayette
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  4. 2024
    Rapid context inference in a thalamocortical model using recurrent neural networksWei‐Long Zheng, Zhongxuan Wu, Ali Hummos … Michael M. HalassaNature Communications · Shanghai Jiao Tong University · Massachusetts Institute of Technology · +3
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  5. 2024
    Wake-Sleep Energy Based Models for Continual LearningVaibhav Singh, Anna Choromanska, Shuang Li, Yilun DuCVPR · Centre Universitaire de Mila · New York University · +2
  6. 2024
    A collective AI via lifelong learning and sharing at the edgeAndrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman … Soheil KolouriNature Machine Intelligence · Loughborough University · Rice University · +21
  7. 2023
    Rapid Learning Without Catastrophic Forgetting in Multiple Morris Water MazesRaymond Wang, Jaedong Hwang, Akhilan Boopathy, Ila FieteConference on Cognitive Computational Neuroscience · Massachusetts Institute of Technology
  8. 2022
    Biological underpinnings for lifelong learning machinesDhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb … Hava T. SiegelmannNature Machine Intelligence · The University of Texas at San Antonio · Intelligent Systems Research (United States) · +24
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  9. 2022
    Thalamocortical contribution to flexible learning in neural systemsMien Brabeeba Wang, Michael M. HalassaNetwork Neuroscience · Massachusetts Institute of Technology
  10. 2021
    Lifelong Personalization via Gaussian Process Modeling for Long-Term HRISamuel Spaulding, Jocelyn Shen, Hae Won Park, Cynthia BreazealFrontiers · Massachusetts Institute of Technology
  11. 2021
    Toward Robust and Efficient Online Adaptation for Deep Stereo Depth EstimationMilo Knowles, Valentin Peretroukhin, W. Nicholas Greene, Nicholas RoyICRA · Massachusetts Institute of Technology
  12. 2021
    Reproducibility Report: La-MAML: Look-ahead Meta Learning for Continual LearningJoel Joseph, Alex GuarXiv · Indian Institute of Technology BHU · Banaras Hindu University · +1
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  13. 2022
    Energy-Based Models for Continual LearningShuang Li, Yilun Du, Gido M. van de Ven, Igor MordatchCoLLAs · Massachusetts Institute of Technology
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  14. 2019
    Toward an AI Physicist for Unsupervised LearningTailin Wu, Max TegmarkPhysical review. E · Theiss Research · Massachusetts Institute of Technology
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  15. 2020
    LAMOL: LAnguage MOdeling for Lifelong Language LearningFan-Keng Sun, Cheng-Hao Ho, Hung-yi LeeICLR · Massachusetts Institute of Technology · National Taiwan University
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  16. 2019
    Continual Learning with Self-Organizing MapsPouya Bashivan, Martin Schrimpf, Robert Ajemian … Yuhai TuarXiv · Massachusetts Institute of Technology
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  17. 2019
    Learning to Learn without Forgetting By Maximizing Transfer and Minimizing InterferenceMatthew Riemer, Ignacio Cases, Robert Ajemian … Gerald TesauroICLR · IBM (United States) · Stanford University · +2
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  18. 2018
    Distributed Weight Consolidation: A Brain Segmentation Case StudyPatrick McClure, Charles Zheng, Jakub Kaczmarzyk … Francisco PereiraNeurIPS · National Institutes of Health · Massachusetts Institute of Technology
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  19. 2017
    Habituation based synaptic plasticity and organismic learning in a quantum perovskiteFan Zuo, Priyadarshini Panda, Michele Kotiuga … Shriram RamanathanNature Communications · Purdue University West Lafayette · Rutgers, The State University of New Jersey · +3
  20. 2008
    Dynamic visual category learningTom Yeh, Trevor DarrellCVPR · Massachusetts Institute of Technology · University of California, Berkeley
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.