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. 2022
    Rethinking Few-Shot Class-Incremental Learning With Open-Set Hypothesis in Hyperbolic GeometryYawen Cui, Zitong Yu, Wei Peng … Li LiuIEEE Trans. Multimedia · University of Oulu · Great Bay University · +3
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  2. 2022
    FIG-LP: Feature-Inverse-Graph based Link Prediction in Graph StreamXu Zhang, Xiao-Qiang Xiao, Guowei Li … Jiantong SongIEEE Smartworld, Ubiquitous Intelligence & Computing,… · National University of Defense Technology · Changsha University
  3. 2022
    ICFD: An Incremental Learning Method Based on Data Feature DistributionYunzhe Zhu, Yusong Tan, Xiaoling Li … Xueqin NingIEEE Smartworld, Ubiquitous Intelligence & Computing,… · National University of Defense Technology
  4. 2022
    Similarity-Driven Adaptive Prototypical Network for Class-incremental Few-shot Named Entity RecognitionYifan Chen, Zhan Huang, Minghao Hu … Xicheng LuIEEE 34th International Conference on Tools with Artifici… · National University of Defense Technology · PLA Academy of Military Science
  5. 2022
    LwF4IEE: An Incremental Learning Method for Interactive Event ExtractionJiashun Duan, Xin Zhang, Chi XuInternational Conference on Cyber-Enabled Distributed Com… · National University of Defense Technology
  6. 2022
    A Feature Incremental Learning Method Based on Evidential Reasoning RuleLi Tu, Ruirui Zhao, Jianbin Sun, Jiang JiangInternational Conference on Big Data and Information Anal… · National University of Defense Technology
  7. 2022
    CLLE: A Benchmark for Continual Language Learning Evaluation in Multilingual Machine TranslationHan Zhang, Sheng Zhang, Yang Xiang … Ruifeng XuEMNLP · Harbin Institute of Technology · Peng Cheng Laboratory · +3
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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.