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.

6 papers of 8,653Sort Recent · Most cited
  1. 2026
    Decomposing the Neurons: Activation Sparsity via Mixture of Experts for Continual Test Time AdaptationRongyu Zhang, Aosong Cheng, Y. Luo … Yuan DuAAAI · Hong Kong Polytechnic University · Peking University · +3
    PDF ↗
  2. 2026
    L2-LoRA: Improving Low-Rank Adaptation with Layer-Specific RegularizationXiang Zhang, Rui Xie, Siyuan ZhangAAAI · Peking University
    PDF ↗
  3. 2024
    Continual Vision-Language Retrieval via Dynamic Knowledge RectificationZhenyu Cui, Yuxin Peng, Xun Wang … Jiahuan ZhouAAAI · Peking University
    PDF ↗
  4. 2024
    Adaptive Discovering and Merging for Incremental Novel Class DiscoveryGuangyao Chen, Peixi Peng, Yangru Huang … Yonghong TianAAAI · Peking University · Peng Cheng Laboratory
    PDF ↗
  5. 2022
    Adaptive Orthogonal Projection for Batch and Online Continual LearningYiduo Guo, Wenpeng Hu, Dongyan Zhao, Bing LiuAAAI · Peking University · King University · +1
  6. 2021
    Continual Learning by Using Information of Each Class HolisticallyWenpeng Hu, Qi Qin, Mengyu Wang … Bing LiuAAAI · Peking University
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.