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.

10 papers of 6,984Sort Recent · Most cited
  1. 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
  2. 2024
    Evaluating Pretrained Models for Deployable Lifelong LearningKiran Lekkala, Eshan Bhargava, Laurent IttiWACV · University of Southern California
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  3. 2023
    CLR: Channel-wise Lightweight Reprogramming for Continual LearningYunhao Ge, Yuecheng Li, Shuo Ni … Laurent IttiICCV · University of Southern California · California Southern University · +1
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  4. 2023
    Batch Model Consolidation: A Multi-Task Model Consolidation FrameworkIordanis Fostiropoulos, Jiaye Zhu, Laurent IttiCVPR · University of Southern California
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  5. 2022
    incDFM: Incremental Deep Feature Modeling for Continual Novelty DetectionAmanda Rios, Nilesh Ahuja, Ibrahima J. Ndiour … Omesh TickooECCV · University of Southern California · Intel (United States)
  6. 2022
    Beneficial Perturbation Network for Designing General Adaptive Artificial Intelligence SystemsShixian Wen, Amanda Rios, Yunhao Ge, Laurent IttiTNNLS · University of Southern California
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  7. 2020
    Lifelong Learning Without a Task OracleAmanda Rios, Laurent IttiIEEE 32nd International Conference on Tools with Artifici… · University of Southern California
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  8. 2019
    Closed-Loop Memory GAN for Continual LearningAmanda Rios, Laurent IttiIJCAI · University of Southern California · California Southern University
  9. 2019
    Beneficial perturbation network for continual learningShixian Wen, Laurent IttiarXiv · University of Southern California · California Southern University
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  10. 2018
    Closed-Loop GAN for continual LearningAmanda Rios, Laurent IttiarXiv · University of Southern California · California Southern University
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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.