Related work

The foundational work on continual learning, 1959 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

18 papers of 11,817Sort Recent · Most cited
  1. 2023
    Visually Grounded Continual Language Learning with Selective SpecializationK. Ahrens, Lennart Bengtson, Jae Hee Lee, Stefan WermterEMNLP
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  2. 2023
    CITB: A Benchmark for Continual Instruction TuningZihan Zhang, Meng Fang, Ling Chen, Mohammad-Reza Namazi-RadEMNLP
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  3. 2023
    Continual Named Entity Recognition without Catastrophic ForgettingDu-Zhen Zhang, Wei Cong, Jia-Hua Dong … Zhen FangEMNLP
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  4. 2023
    Coordinated Replay Sample Selection for Continual Federated LearningJack H. Good, Jimit Majmudar, Christophe Dupuy … Rahul GuptaEMNLP
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  5. 2023
    Orthogonal Subspace Learning for Language Model Continual LearningXiao Wang, Tianze Chen, Qiming Ge … Xuanjing HuangEMNLP
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  8. 2023
    Sub-network Discovery and Soft-masking for Continual Learning of Mixed TasksZixuan Ke, Bing Liu, Wenhan Xiong … Haoran LiEMNLP
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  9. 2023
    Rationale-Enhanced Language Models are Better Continual Relation LearnersWeimin Xiong, Yifan Song, Peiyi Wang, Sujian LiEMNLP
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  10. 2023PDF ↗
  11. 2023
    Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data CurationDa Yin, Xiao Liu, Fan Yin … Kai-Wei ChangEMNLP
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  12. 2023
    Continual Dialogue State Tracking via Example-Guided Question AnsweringHyundong Justin Cho, Andrea Madotto, Zhaojiang Lin … Chinnadhurai SankarEMNLP
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  16. 2023
    Causal Intervention-based Few-Shot Named Entity RecognitionZhen Yang, Yongbin Liu, Chunping OuyangEMNLP
  17. 2023
  18. 2023
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.