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. 2026
    Structure-aware federated hypergraph continual learningYanxin Hu, Xiaoman Liu, Zhenzhen Xie … Chao ChengInformation Sciences · Changchun University of Technology · Shandong University of Science and Technology · +3
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  2. 2026
    SA-LoRA: Shared-A decoupled low-rank adaptation for class-incremental learningXiaohuan Bing, Yuanhao Xi, Ramin YahyapourInformation Sciences · Liaoning Technical University · University of Göttingen · +1
  3. 2026
    Distribution-aware sampling of replay buffer for mitigating catastrophic forgettingArmaan Garg, Ansh Raj Sharma, Aryan Arora, Shilpa VermaInformation Sciences · Dr. B. R. Ambedkar National Institute of Technology Jalandhar · Punjab Engineering College
  4. 2026
    TADG: topology-aware and distillation-guided framework for continual knowledge graph embeddingMingsheng Wang, Pengfei Wang, Ming He, Hongbin WangInformation Sciences · Harbin Engineering University · Tokyo Institute of Technology
  5. 2026
    LUNCH: adaptive balancing of continual learning via hyperparameter uncertaintyQingyi Pan, Liyuan Wang, Jingyi Zhang, Jun ZhuInformation Sciences · Tsinghua University · Beijing University of Posts and Telecommunications
  6. 2026
    CRAD-HOPE: brain-inspired nested learning framework for few-shot anomaly detectionWenxin Cao, Juanhua Cao, Weijun WuInformation Sciences · University of Electronic Science and Technology of China · Jiangxi College of Applied Technology · +1
  7. 2026
    RSCL: Adaptive meta-learning framework inspired by rough set theory and continual learningL. L. Ding, Shuliang ZhaoInformation Sciences · Hebei University of Economics and Business · Hebei Normal University
  8. 2026
    Online label aggregation with incomplete crowd responsesYuyang Liu, Haoyu Liu, Runze Wu … Changjie FanInformation Sciences · Chinese Academy of Medical Sciences & Peking Union Medical College · NetEase (China) · +1
  9. 2026
    Class semantics guided knowledge distillation for few-shot class incremental learningPing Li, Jiajun Chen, Shaoqi Tian, Ran WangInformation Sciences · Hangzhou Dianzi University · Nanjing 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.