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. 2024
    Class-Incremental Few-Shot Event DetectionKailin Zhao, Xiaolong Jin, Long Bai … Xueqi ChengInternational Conference on Language Resources and Evalua…
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  2. 2024
    Mixture-of-LoRAs: An Efficient Multitask Tuning Method for Large Language ModelsWenfeng Feng, Chuzhan Hao, Yuewei Zhang … Hao WangInternational Conference on Language Resources and Evalua…
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  3. 2024
    DP-CRE: Continual Relation Extraction via Decoupled Contrastive Learning and Memory Structure PreservationHuang, Mengyi, Meng Xiao, Ludi Wang, Yi DuInternational Conference on Language Resources and Evalua…
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  4. 2024
    Making Pre-trained Language Models Better Continual Few-Shot Relation ExtractorsShengkun Ma, Jiale Han, Yi Liang, Bo ChengInternational Conference on Language Resources and Evalua…
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  5. 2024
    MemoryPrompt: A Light Wrapper to Improve Context Tracking in Pre-trained Language ModelsNathanaël Carraz Rakotonirina, Marco BaroniInternational Conference on Language Resources and Evalua…
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  6. 2023
    Retentive or Forgetful? Diving into the Knowledge Memorizing Mechanism of Language ModelsBoxi Cao, Qiaoyu Tang, Hongyu Lin … Le SunInternational Conference on Language Resources and Evalua…
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  7. 2020
    An Evaluation of Progressive Neural Networksfor Transfer Learning in Natural Language ProcessingAbdul Moeed, Gerhard Johann Hagerer, S. Dugar … Georg GrohInternational Conference on Language Resources and Evalua…
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.