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.

41 papers of 11,817Sort Recent · Most cited
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    Interactive Visual Task Learning for RobotsWei-Wei Gu, Anant Sah, N. GopalanAAAI
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    Doubly Perturbed Task-Free Continual LearningByung Hyun Lee, Min-hwan Oh, Se-Young ChunAAAI
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    What to Remember: Self-Adaptive Continual Learning for Audio Deepfake DetectionXiaohui Zhang, Jiangyan Yi, Chenglong Wang … Jianhua TaoAAAI
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    Exploiting Symmetric Temporally Sparse BPTT for Efficient RNN TrainingXi Chen, Chang Gao, Zuowen Wang … Tobi DelbruckAAAI
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    Adaptive Shortcut Debiasing for Online Continual LearningDoyoung Kim, Dongmin Park, Yooju Shin … Jae-Gil LeeAAAI
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    LAMM: Label Alignment for Multi-Modal Prompt LearningJingsheng Gao, Jiacheng Ruan, Suncheng Xiang … Yuzhuo FuAAAI
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    MIND: Multi-Task Incremental Network DistillationJacopo Bonato, Francesco Pelosin, Luigi Sabetta, Alessandro NicolosiAAAI
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    Online Noisy Continual Relation LearningGuozheng Li, Peifeng Wang, Qiqing Luo … Wenjun KeAAAI
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    Meta-Auxiliary Learning for Adaptive Human Pose PredictionQiongjie Cui, Huaijiang Sun, Jianfeng Lu … Weiqing LiAAAI
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    Online Hyperparameter Optimization for Class-Incremental LearningYaoyao Liu, Ying-Ying Li, B. Schiele, Qianru SunAAAI
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    From Continual Learning to Causal Discovery in RoboticsLuca Castri, Sariah Mghames, N. BellottoAAAI
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    Towards Causal Replay for Knowledge Rehearsal in Continual LearningNikhil Churamani, Jiaee Cheong, Sinan Kalkan, Hatice GunesAAAI
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    Issues for Continual Learning in the Presence of Dataset BiasDonggyu Lee, Sangwon Jung, Taesup MoonAAAI
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    From IID to the Independent Mechanisms assumption in continual learningOleksiy Ostapenko, Pau Rodríguez López, Alexandre Lacoste, Laurent CharlinAAAI
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    Treatment Effect Estimation to Guide Model Optimization in Continual LearningJonas Seng, Florian Peter Busch, M. Zecevic, Moritz WilligAAAI
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.