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. 2022
    PIVOT: Prompting for Video Continual LearningAndrés Villa, Juan León Alcázar, Motasem Alfarra … Bernard GhanemCVPR · Pontificia Universidad Católica de Chile · King Abdullah University of Science and Technology · +2
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  2. 2022
    D3Former: Debiased Dual Distilled Transformer for Incremental LearningAbdelrahman Mohamed, Rushali Grandhe, K. J. Joseph … Fahad Shahbaz KhanCVPR · Mohamed bin Zayed University of Artificial Intelligence · Adobe Systems (United States) · +1
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  3. 2022
    Graph Deep Factors for Probabilistic Time-series ForecastingHongjie Chen, Ryan A. Rossi, Kanak Mahadik … Hoda EldardiryACM Transactions · Virginia Tech · Adobe Systems (United States)
  4. 2022
    vCLIMB: A Novel Video Class Incremental Learning BenchmarkAndrés Villa, Kumail Alhamoud, Víctor Escorcia … Bernard GhanemCVPR · Pontificia Universidad Católica de Chile · King Abdullah University of Science and Technology · +2
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  5. 2022
    CGC: Contrastive Graph Clustering forCommunity Detection and TrackingNamyong Park, Ryan A. Rossi, Eunyee Koh … Christos FaloutsosACM Web Conference 2022 · Carnegie Mellon University · Adobe Systems (United States) · +1
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  6. 2022
    Few-Shot Class-Incremental Learning for Named Entity RecognitionRui Wang, Tong Yu, Handong Zhao … Ricardo HenaoACL · Duke University · Adobe Systems (United States)
  7. 2022
    Bridging Images and Videos: A Simple Learning Framework for Large Vocabulary Video Object DetectionSanghyun Woo, Kwanyong Park, Seoung Wug Oh … Joon‐Young LeeSpringer LNCS · Korea Advanced Institute of Science and Technology · Adobe Systems (United States)
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  8. 2021
    Few-Shot Continual Learning for Audio ClassificationYu Wang, Nicholas J. Bryan, Mark Cartwright … Justin SalamonICASSP · New York University · Adobe Systems (United States)
  9. 2019
    Lifelong Learning with a Changing Action SetYash Chandak, Georgios Theocharous, Chris Nota, Philip S. ThomasAAAI · University of Massachusetts Amherst · Adobe Systems (United States)
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  10. 2019
    REMIND Your Neural Network to Prevent Catastrophic ForgettingTyler L. Hayes, Kushal Kafle, Robik Shrestha … Christopher KananSpringer LNCS · Rochester Institute of Technology · Adobe Systems (United States) · +2
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  11. 2020
    M2KD: Incremental Learning via Multi-model and Multi-level Knowledge DistillationPeng Zhou, Long Mai, Jianming Zhang … Larry S. DavisBMVC · Beth Israel Deaconess Medical Center · Adobe Systems (United States) · +2
  12. 2019
    A Scalable Data Augmentation and Training Pipeline for Logo DetectionHan Guo, Viswanathan Swaminathan, Saayan MitraIEEE International Symposium on Multimedia (ISM) · Adobe Systems (United States)
  13. 2018
    Deep Face Detector Adaptation Without Negative Transfer or Catastrophic ForgettingMuhammad Abdullah Jamal, Haoxiang Li, Boqing GongJournal of International Crisis and Risk Communication Re… · University of Central Florida · Adobe Systems (United States) · +1
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.