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. 2026
    Scalable Expansion of Multilingual Speech LLMs for ASR: A Continual Learning ApproachLorenzo Concina, Marco Matassoni, Alessio BruttiLanguage Resources and Evaluation Conference · Fondazione Bruno Kessler
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  2. 2024
    Continual Reinforcement Learning for Controlled Text GenerationVelizar Shulev, Khalil Sima’anLanguage Resources and Evaluation Conference
  3. 2024
    Distilling Causal Effect of Data in Continual Few-shot Relation LearningWeihang Ye, Peng Zhang, Jing Zhang … Moyao WangLanguage Resources and Evaluation Conference
  4. 2024
    Enhancing Translation Ability of Large Language Models by Leveraging Task-Related LayersPei Cheng, Xiayang Shi, Yinlin LiLanguage Resources and Evaluation Conference
  5. 2024
    Improving Continual Few-shot Relation Extraction through Relational Knowledge Distillation and Prototype AugmentationZhiheng Zhang, Daojian Zeng, Xue BaiLanguage Resources and Evaluation Conference
  6. 2024
    Depth Aware Hierarchical Replay Continual Learning for Knowledge Based Question AnsweringZhixiong Cao, Hai-Tao Zheng, Yangning Li … Hong-Gee KimLanguage Resources and Evaluation Conference
  7. 2024
    STAF: Pushing the Boundaries of Test-Time Adaptation towards Practical Noise ScenariosHaoyu Xiong, Xinchun Zhang, Leixin Yang … Gang FangLanguage Resources and Evaluation Conference
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. By default it shows the papers we have a reason to trust: published at a venue like NeurIPS, ICML, ICLR, CVPR or TPAMI, or written by someone who has published there, or cited a few hundred times. The rest are one click away under “All papers”. 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.