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.

8 papers of 8,653Sort Recent · Most cited
  1. 2021
    Continual Learning for Text Classification with Information Disentanglement Based RegularizationYufan Huang, Yanzhe Zhang, Jiaao Chen … Diyi YangNAACL · Georgia Institute of Technology · Google (United States) · +1
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  2. 2021
    Adapting BERT for Continual Learning of a Sequence of Aspect Sentiment Classification TasksZixuan Ke, Hu Xu, Bing LiuNAACL · University of Illinois Chicago · Meta (Israel)
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  3. 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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  4. 2021
    Towards Continual Learning for Multilingual Machine Translation via Vocabulary SubstitutionXavier García, Noah Constant, Ankur P. Parikh, Orhan FıratNAACL · Google (United States)
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  5. 2021
    Continual Learning for Neural Machine TranslationYue Cao, Haoran Wei, Boxing Chen, Xiaojun WanNAACL · Peking University · Alibaba Group (United States)
  6. 2021
    Pruning-then-Expanding Model for Domain Adaptation of Neural Machine TranslationShuhao Gu, Yang Feng, Wanying XieNAACL · Chinese Academy of Sciences · Institute of Computing Technology · +2
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  7. 2021
    Lifelong Learning of Hate Speech Classification on Social MediaJing Qian, Hong Wang, Mai ElSherief, Xifeng YanNAACL · Georgia Institute of Technology · University of California, Santa Barbara
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  8. 2021
    Hyperparameter-free Continuous Learning for Domain Classification in Natural Language UnderstandingTing Hua, Yilin Shen, Changsheng Zhao … Hongxia JinNAACL · Samsung (United States) · Research!America (United States)
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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.