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.

9 papers of 8,653Sort Recent · Most cited
  1. 2025
    Continual Learning for VLMs: A Survey and Taxonomy Beyond ForgettingYuyang Liu, Qiuhe Hong, Linlan Huang … Yonghong TianarXiv
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  2. 2025
    Query Drift Compensation: Enabling Compatibility in Continual Learning of Retrieval Embedding ModelsDipam Goswami, Liying Wang, Bartłomiej Twardowski, Joost van de WeijerarXiv
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  3. 2024
    Exemplar-free Continual Representation Learning via Learnable Drift CompensationAlex Gomez-Villa, Dipam Goswami, Kai Wang … Joost van de WeijerECCV
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  4. 2024PDF ↗
  5. 2024
    Resurrecting Old Classes with New Data for Exemplar-Free Continual LearningDipam Goswami, Albin Soutif--Cormerais, Yuyang Liu … Joost van de WeijerCVPR · University of Chinese Academy of Sciences
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  6. 2023PDF ↗
  7. 2023
    Augmented Box Replay: Overcoming Foreground Shift for Incremental Object DetectionYuyang Liu, Yang Cong, Dipam Goswami … Joost van de WeijerICCV · Shenyang Institute of Automation · Chinese Academy of Sciences · +4
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  8. 2023
    FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual LearningDipam Goswami, Yuyang Liu, Bartłomiej Twardowski, Joost van de WeijerNeurIPS
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  9. 2022
    Attribution-aware Weight Transfer: A Warm-Start Initialization for Class-Incremental Semantic SegmentationDipam Goswami, René Schuster, Joost van de Weijer, Didier StrickerWACV · German Research Centre for Artificial Intelligence · Birla Institute of Technology and Science, Pilani · +2
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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 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.