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. 2024
    Federated Class-Incremental Learning with New-Class Augmented Self-DistillationZhiyuan Wu, Tianliu He, Sheng Sun … Xuefeng JiangJournal of Computer Science and Technology · Chinese Academy of Sciences · Institute of Computing Technology · +2
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  2. 2024
    Incremental Learning via Robust Parameter Posterior FusionWenju Sun, Qingyong Li, Siyu Zhang … Yangli-ao GengACM International Conference on Multimedia · Beijing Jiaotong University
  3. 2024
    Generative Replay and Multi-steps Knowledge Distillation in Class-Incremental LearningYicheng Meng, J. L. Ping, Jingye Shi, Ruicong Zhi2024 3rd International Conference on Artificial Intellige… · University of Science and Technology Beijing · Beijing Jiaotong University
  4. 2024
    Fast and Continual Knowledge Graph Embedding via Incremental LoRAXudong Yan, Songhe Feng, Yang Zhang … Haojun FeiIJCAI · Beijing Jiaotong University · Qilu University of Technology · +3
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  5. 2024
    Continual Compositional Zero-Shot LearningDonghao Luo, Yujie Liang, Xu Peng … Yanwei FuIJCAI · Beijing Jiaotong University · Tencent (China) · +3
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  6. 2024
    Continual Learning with Confidence-based Multi-teacher Knowledge Distillation for Neural Machine TranslationJiahua Guo, Yunlong Liang, Jinan XuInternational Conference on Natural Language Processing (… · Beijing Jiaotong University
  7. 2024
    Continual Learning with Semi-supervised Contrastive Distillation for Incremental Neural Machine TranslationYunlong Liang, Fandong Meng, Jiaan Wang … Jie ZhouACL · Beijing Jiaotong University · Tencent (China)
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  8. 2024
    ICL: Iterative Continual Learning for Multi-domain Neural Machine TranslationZhibo Man, Kaiyu Huang, Yujie Zhang … Jinan XuEMNLP · Beijing Jiaotong University
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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.