Related work

The foundational work on continual learning, 1988 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

10 papers of 6,984Sort Recent · Most cited
  1. 2026
    ORACIL: Conflict-Graph-Based Order-Robust Analytic Class-Incremental LearningGuanjie Wang, Hongyu Sun, Weiwei Li, Yanhua DongElectronics · Jilin Normal University
  2. 2026
    PILOT: A Replay-Free Continual Learning Approach for Real-Time Semantic Segmentation via Boundary GuidanceYujing Zhou, Prashant Shekhar, Thomas Yang, Yongxin LiuElectronics · Embry–Riddle Aeronautical University
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  3. 2025
    DPAO-PFL: Dynamic Parameter-Aware Optimization via Continual Learning for Personalized Federated LearningJialu Tang, Yali Gao, Xiaoyong Li, Jia JiaElectronics · Beijing University of Posts and Telecommunications
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  4. 2025
    Joint Event Detection with Dynamic Adaptation and Semantic RelevanceXi Zeng, Guangchun Luo, Ke QinElectronics · University of Electronic Science and Technology of China · China Electronics Technology Group Corporation
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  5. 2024PDF ↗
  6. 2024
    NLOCL: Noise-Labeled Online Continual LearningKan Cheng, Yongxin Ma, Guanglu Wang … Xinyue LiuElectronics · China Academy of Space Technology · Dalian University of Technology
  7. 2024
    FedSKF: Selective Knowledge Fusion via Optimal Transport in Federated Class Incremental LearningMinghui Zhou, Xiangfeng WangElectronics · East China Normal University
  8. 2023
    Few Shot Class Incremental Learning via Grassmann Manifold and Information EntropyZiqi Gu, Zihan Lu, Han Cao, Chunyan XuElectronics · Nanjing University of Science and Technology
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  9. 2021
    Two-Branch Attention Learning for Fine-Grained Class Incremental LearningJiaqi Guo, Guanqiu Qi, Xie Shuiqing, Xiangyuan LiElectronics · South Central Minzu University · Buffalo State University · +1
  10. 2021
    Progressive Convolutional Neural Network for Incremental LearningZahid Ali Siddiqui, Unsang ParkElectronics · Sogang 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 lists only papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or led by someone who has published there, or cited a few hundred times. Preprints that later get accepted, and authors who later publish at those venues, are picked up by the weekly run. 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.