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.

16 papers of 6,984Sort Recent · Most cited
  1. 2023
    CITB: A Benchmark for Continual Instruction TuningZihan Zhang, Meng Fang, Ling Chen, Mohammad‐Reza Namazi‐RadEMNLP
    PDF ↗
  2. 2023
    Continual Named Entity Recognition without Catastrophic ForgettingDuzhen Zhang, Cong Wei, Jiahua Dong … Zhen FangEMNLP
    PDF ↗
  3. 2023
    Coordinated Replay Sample Selection for Continual Federated LearningJack Good, Jimit Majmudar, Christophe Dupuy … Rahul GuptaEMNLP
    PDF ↗
  4. 2023
    Orthogonal Subspace Learning for Language Model Continual LearningXinghuan Wang, Tianze Chen, Qiming Ge … Xuanjing HuangEMNLP
    PDF ↗
  5. 2023PDF ↗
  6. 2023
    Sub-network Discovery and Soft-masking for Continual Learning of Mixed TasksZixuan Ke, Bing Liu, Wenhan Xiong … Haoran LiEMNLP
    PDF ↗
  7. 2023
    Rationale-Enhanced Language Models are Better Continual Relation LearnersWeimin Xiong, Yifan Song, Peiyi Wang, Sujian LiEMNLP
    PDF ↗
  8. 2023PDF ↗
  9. 2023
    Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data CurationDa Yin, Xiao Liu, Fan Yin … Kai-Wei ChangEMNLP
    PDF ↗
  10. 2023
    Continual Dialogue State Tracking via Example-Guided Question AnsweringHyundong Cho, Andrea Madotto, Zhaojiang Lin … Chinnadhurai SankarEMNLP
    PDF ↗
  11. 2023PDF ↗
  12. 2023PDF ↗
  13. 2023
    Continual Learning for Multilingual Neural Machine Translation via Dual Importance-based Model DivisionJunpeng Liu, Kaiyu Huang, Hao Yu … Degen HuangEMNLP · Dalian University of Technology · Tsinghua University · +1
    PDF ↗
  14. 2023
    Visually Grounded Continual Language Learning with Selective SpecializationKyra Ahrens, Lennart Bengtson, Jae Yeol Lee, Stefan WermterEMNLP · Universität Hamburg
    PDF ↗
  15. 2023
    Incorporating Syntactic Knowledge into Pre-trained Language Model using Optimization for Overcoming Catastrophic ForgettingRan Iwamoto, Issei Yoshida, Hiroshi Kanayama … Masayasu MuraokaEMNLP · Keio University · IBM Research - Tokyo
    PDF ↗
  16. 2023
    DSI++: Updating Transformer Memory with New DocumentsSanket Vaibhav Mehta, Jai Prakash Gupta, Yi Tay … Donald MetzlerEMNLP
    PDF ↗
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.