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. 2021
    Conflicts between Likelihood and Knowledge Distillation in Task Incremental Learning for 3D Object DetectionYun Peng, Jun Cen, Ming LiuInternational Conference on 3D Vision (3DV) · Hong Kong University of Science and Technology
  2. 2021
    Deep Metric Learning for Open World Semantic SegmentationJun Cen, Yun Peng, Junhao Cai … Ming LiuICCV · Hong Kong University of Science and Technology · Sun Yat-sen University
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  3. 2021
    Continual learning classification method for time-varying data space based on artificial immune systemDong Li, Shulin Liu, Furong Gao, Xin SunJournal of Intelligent & Fuzzy Systems · Hong Kong University of Science and Technology · Changzhou University · +1
  4. 2021
    In Defense of Knowledge Distillation for Task Incremental Learning and Its Application in 3D Object DetectionYun Peng, Yuxuan Liu, Ming LiuRA-L · Hong Kong University of Science and Technology
  5. 2021
    AdaptSum: Towards Low-Resource Domain Adaptation for Abstractive SummarizationTiezheng Yu, Zihan Liu, Pascale FungNAACL · Hong Kong University of Science and Technology
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  6. 2021
    Preserving Cross-Linguality of Pre-trained Models via Continual LearningZihan Liu, Genta Indra Winata, Andrea Madotto, Pascale FungWorkshop on Representation Learning for NLP (RepL4NLP-2021) · Hong Kong University of Science and Technology
  7. 2021
    Continual learning classification method with constant-sized memory cells based on the artificial immune systemDong Li, Shulin Liu, Furong Gao, Xin SunKnowledge-Based Systems · Hong Kong University of Science and Technology · Changzhou University · +1
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.