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.

7 papers of 8,653Sort Recent · Most cited
  1. 2026
    Multi-Stage Knowledge Integration of Vision-Language Models for Continual LearningHongsheng Zhang, Zhong Ji, Jingren Liu … Jungong HanTIP · Tianjin University · Tsinghua University
    PDF ↗
  2. 2026
    Dual Domain-Attribute Learning Framework With Asynchronous Adapters for Continual Test-Time AdaptationYuntong Tian, Kang Li, Tianyang He … Wei FengTIP · Tianjin University · University of Electronic Science and Technology of China · +1
  3. 2024
    Layer-Specific Knowledge Distillation for Class Incremental Semantic SegmentationQilong Wang, Yiwen Wu, Yang Liu … Qinghua HuTIP · Tianjin University · Harbin Institute of Technology · +1
  4. 2024
    NTK-Guided Few-Shot Class Incremental LearningJingren Liu, Zhong Ji, Yanwei Pang, Yunlong YuTIP · Tianjin University · Zhejiang University
    PDF ↗
  5. 2024
    Model Attention Expansion for Few-Shot Class-Incremental LearningXuan Wang, Zhong Ji, Yunlong Yu … Jungong HanTIP · Tianjin University · Zhejiang University · +1
  6. 2023
    Memorizing Complementation Network for Few-Shot Class-Incremental LearningZhong Ji, Zhishen Hou, Xiyao Liu … Xuelong LiTIP · Tianjin University · Shenyang Institute of Automation · +2
    PDF ↗
  7. 2022
    Complementary Calibration: Boosting General Continual Learning With Collaborative Distillation and Self-SupervisionZhong Ji, Jin Li, Qiang Wang, Zhongfei ZhangTIP · Tianjin University · Binghamton University
    PDF ↗
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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.