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.

31 papers of 11,817Sort Recent · Most cited
  1. 2026
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    Cross Task Knowledge Transfer for Rehearsal-Free Continual LearningShuai Chen, Leike An, Jiaxin Wang … Jibin WangICASSP
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    Revisiting Prototypes for Open-Domain Continual Learning in Vision-Language ModelsYadong Lu, Shitian Zhao, Boxiang Yun … Yan WangICASSP
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    Semantic and Temporal-Aware Distillation for Class-Incremental LearningDongyan Guo, Xu-Sheng Wang, Yuanhao Zheng … Ying CuiICASSP
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    Incremental learning for audio classification with Hebbian Deep Neural NetworksRiccardo Casciotti, F. De Santis, A. Antonietti, A. MesarosICASSP
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  26. 2026
    FadeMem: Biologically-Inspired Forgetting for Efficient Agent MemoryLei Wei, Xu Dong, Xiao Peng … Bin WangICASSP
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  27. 2026
    FGGM: Fisher-Guided Gradient Masking for Continual LearningChaohong Tan, Qian Chen, Wen Wang … Jieping YeICASSP
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  28. 2026PDF ↗
  29. 2026
    Inverse-Hessian Regularization for Continual Learning in ASRSteven Vander Eeckt, Hugo Van hammeICASSP
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  30. 2026
    DistilMOS: Layer-Wise Self-Distillation For Self-Supervised Learning Model-Based MOS PredictionJianing Yang, Wataru Nakata, Yuki Saito, Hiroshi SaruwatariICASSP
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  31. 2026PDF ↗
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.