Related work

The foundational work on continual learning, 1989 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

9 papers of 5,456Sort Recent · Most cited
  1. 2025
    SPOT: An efficient training-free task similarity quantification method for continual learningXulong Wang, Yu Zhang, Tong Liu … Po YangPattern Recognition Letters · University of Sheffield · Hong Kong Polytechnic University
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  2. 2025
    Re-examine all-in-one image restoration: A catastrophic forgetting perspectiveChen Wu, Pu Wang, Zhuoran ZhengPattern Recognition Letters · University of Science and Technology of China · Shandong University · +2
  3. 2024
    FCL-ViT: Task-Aware Attention Tuning for Continual LearningAnestis Kaimakamidis, Ioannis PitasPattern Recognition Letters
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  4. 2024
    CaSpeR: Latent Spectral Regularization for Continual LearningEmanuele Frascaroli, Riccardo Benaglia, Matteo Boschini … Simone CalderaraPattern Recognition Letters · University of Modena and Reggio Emilia · Sapienza University of Rome
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  5. 2024
    PNSP: Overcoming catastrophic forgetting using Primary Null Space Projection in continual learningDaiLiang Zhou, Yonghong SongPattern Recognition Letters · Xi'an Jiaotong University
  6. 2022
    Rethinking class orders and transferability in class incremental learningChen He, Ruiping Wang, Xilin ChenPattern Recognition Letters · Chinese Academy of Sciences · Institute of Computing Technology · +1
  7. 2021
    Continual semi-supervised learning through contrastive interpolation consistencyMatteo Boschini, Pietro Buzzega, Lorenzo Bonicelli … Simone CalderaraPattern Recognition Letters · University of Modena and Reggio Emilia
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  8. 2021
    ACAE-REMIND for Online Continual Learning with Compressed Feature ReplayKai Wang, Joost van de Weijer, Luis HerranzPattern Recognition Letters · Universitat Autònoma de Barcelona · Computer Vision Center
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  9. 2020
    Faster ILOD: Incremental Learning for Object Detectors based on Faster RCNNCan Peng, Kun Zhao, Brian C. LovellPattern Recognition Letters · The University of Queensland
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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 written 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.