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.

8 papers of 11,817Sort Recent · Most cited
  1. 2024
    APM: Adaptive parameter multiplexing for class incremental learningJinghan Gao, Tao Xie, Ruifeng Li … Li-jun ZhaoExpert Systems with Applications
  2. 2024
    The deep continual learning framework for prediction of blast-induced overbreak in tunnel constructionBiao He, Jialu Li, D. J. Armaghani … Dai-Chao ShengExpert Systems with Applications
  3. 2024
    A flexible enhanced fuzzy min-max neural network for pattern classificationEssam Alhroob, Mohammed Falah Mohammed, Osama Nayel Al Sayaydeh … C. LimExpert Systems with Applications
  4. 2024
    Rethinking few-shot class-incremental learning: A lazy learning baselineZhili Qin, Wei Han, Jiaming Liu … Jun-Ming ShaoExpert Systems with Applications
  5. 2024
    Balanced Residual Distillation Learning for 3D Point Cloud Class-Incremental Semantic SegmentationYuanzhi Su, Siyuan Chen, Yuan-Gen WangExpert Systems with Applications
    PDF ↗
  6. 2024
  7. 2024
    Continual test-time adaptation for object detection with adaptive monitoring and randomized restorationShi-Lei Cao, Juepeng Zheng, Yan Liu … Haohuan FuExpert Systems with Applications
    PDF ↗
  8. 2024
    Class-incremental learning with causal relational replayToàn Nguyên, D. Kieu, Bao Duong … Hoai Bac LeExpert Systems with Applications
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.