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.

7 papers of 11,817Sort Recent · Most cited
  1. 2024
    Temporal Transformer Encoder for Video Class Incremental LearningNattapong Kurpukdee, A. BorsInternational Conference on Information Photonics
  2. 2024
    Adversarially Robust Continual Learning with Anti-Forgetting LossKoki Mukai, Soichiro Kumano, Nicolas Michel … Toshihiko YamasakiInternational Conference on Information Photonics
  3. 2024
    Imbalanced Data Robust Online Continual Learning Based on Evolving Class Aware Memory Selection and Built-In Contrastive Representation LearningRui Yang, E. Dellandréa, Matthieu Grard, Li-Ming ChenInternational Conference on Information Photonics
  4. 2024
    Video Class-Incremental Learning With Clip Based TransformerShuyun Lu, Jian Jiao, Lanxiao Wang … Hongliang LiInternational Conference on Information Photonics
  5. 2024
    Conditional Past Experience Generation for Dark Continual LearningChengang Feng, Chaoliang Zhong, Jiexi Wang … Yasuto YokotaInternational Conference on Information Photonics
  6. 2024
    CM2-Net: Continual Cross-Modal Mapping Network for Driver Action RecognitionRuoyu Wang, Chen Cai, Wenqian Wang … Kim-hui YapInternational Conference on Information Photonics
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  7. 2024
    U-TELL: Unsupervised Task Expert Lifelong LearningIndu Solomon, A. P. P. Aung, Uttam Kumar, Senthilnath JayaveluInternational Conference on Information Photonics
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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.