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.

19 papers of 8,653Sort Recent · Most cited
  1. 2024
    Parameter Averaging Is All You Need To Prevent ForgettingPeter Plantinga, Jaekwon Yoo, Abenezer Girma, Chandra DhirIEEE Spoken Language Technology Workshop (SLT) · McGill University · JPMorgan Chase & Co (United States)
  2. 2023
    Hessian Aware Low-Rank Perturbation for Order-Robust Continual LearningJiaqi Li, Yuanhao Lai, Rui Wang … Fan ZhouTKDE · Western University · Vector Institute · +3
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  3. 2020
    Towards Continual Reinforcement Learning: A Review and PerspectivesKhimya Khetarpal, Matthew Riemer, Irina Rish, Doina PrecupJournal of Artificial Intelligence Research · Google DeepMind (United Kingdom) · McGill University · +2
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  4. 2022
    Dynamic Consolidation for Continual LearningHang Li, Chen Ma, Xi Chen, Xue LiuNeural Computation · McGill University · City University of Hong Kong
  5. 2021
    SPeCiaL: Self-Supervised Pretraining for Continual LearningLucas Caccia, Joëlle PineauSpringer LNCS · McGill University
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  6. 2022
    Continual Reinforcement Learning with Multi-Timescale Successor FeaturesRaymond Chua, Blake Richards, Doina Precup, Christos KaplanisConference on Cognitive Computational Neuroscience · McGill University · Google DeepMind (United Kingdom)
  7. 2021
    Impact Patterns of Combining Model Pruning and Continual Learning on Model PerformanceXueyang Zhang, Hang Li, Xi Chen, Xue LiuIEEE Third International Conference on Cognitive Machine… · McGill University
  8. 2021
    Structure Aware Experience Replay for Incremental Learning in Graph-based Recommender SystemsKian Ahrabian, Yishi Xu, Yingxue Zhang … Mark CoatesACM International Conference on Information & Knowled… · McGill University · Huawei Technologies (Canada)
  9. 2021
    Learning offline: memory replay in biological and artificial reinforcement learningEmma L. Roscow, Raymond Chua, Rui Ponte Costa … Nathan F. LeporaTrends in Neurosciences · Centre de Recerca Matemàtica · McGill University · +2
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  10. 2021
    TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph CompletionJiapeng Wu, Yishi Xu, Yingxue Zhang … Jackie Chi Kit CheungSIGIR · McGill University · Université de Montréal · +1
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  11. 2020
    FoCL: Feature-Oriented Continual Learning for Generative ModelsQicheng Lao, Mehrzad Mortazavi, Marzieh S. Tahaei … Mohammad HavaeiPattern Recognition · Sichuan University · West China Medical Center of Sichuan University · +3
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  12. 2021
    Understanding Capacity Saturation in Incremental LearningShenyang Huang, Vincent François-Lavet, Guillaume RabusseauCanadian Conference on Artificial Intelligence · Centre Universitaire de Mila · McGill University · +3
  13. 2020
    GraphSAIL: Graph Structure Aware Incremental Learning for Recommender SystemsYishi Xu, Yingxue Zhang, Wei Guo … Mark CoatesCIKM · Université de Montréal · Huawei Technologies (Canada) · +2
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  14. 2020
    Keynote Lecture - Building Knowledge For AI AgentsWith Reinforcement LearningDoina PrecupIEEE 16th International Conference on Intelligent Compute… · Google DeepMind (United Kingdom) · McGill University
  15. 2020
    Generalisation Guarantees for Continual Learning with Orthogonal Gradient DescentMehdi Bennani, Thang Doan, Masashi SugiyamaarXiv · École Nationale Supérieure des Mines de Paris · McGill University · +1
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  16. 2020
    Evaluating Logical Generalization in Graph Neural NetworksKoustuv Sinha, Shagun Sodhani, Joëlle Pineau, William L. HamiltonarXiv · McGill University
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  17. 2019
    Online Learned Continual Compression with Stacked Quantization ModuleLucas Caccia, Eugene Belilovsky, M. Caccia, Joëlle PineauarXiv · McGill University · Meta (Israel)
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  18. 2019
    Online Continual Learning with Maximally Interfered RetrievalRahaf Aljundi, Lucas Caccia, Eugene Belilovsky … Tinne TuytelaarsarXiv · McGill University · Université de Montréal · +1
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  19. 2019
    Building Knowledge for AI Agents with Reinforcement LearningDoina PrecupAdaptive Agents and Multi-Agents Systems · McGill 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. 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.