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.

12 papers of 11,817Sort Recent · Most cited
  1. 2025
  2. 2025
    Lifelong Learner: Discovering Versatile Neural Solvers for Vehicle Routing ProblemsShaodi Feng, Zhuoyi Lin, Jianan Zhou … Y. OngIEEE T-ITS
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  3. 2025
  4. 2025
    LifelongPR: Lifelong Point Cloud Place Recognition Based on Sample Replay and Prompt LearningXianghong Zou, Jianping Li, Zhe Chen … Bisheng YangIEEE T-ITS
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  5. 2025
    Enhancing Cooperative LiDAR-Based Perception Accuracy in Vehicular Edge NetworksJiawei Hou, Peng Yang, Xiangxiang Dai … Feng LyuIEEE T-ITS
  6. 2025
  7. 2025
    Domain-Incremental Semantic Segmentation for Traffic ScenesYazhou Liu, Hao-Qi Chen, P. Lasang, Zheng WuIEEE T-ITS
  8. 2022
    Continual Interactive Behavior Learning With Traffic Divergence Measurement: A Dynamic Gradient Scenario Memory ApproachYunlong Lin, Zirui Li, Cheng Gong … Jianwei GongIEEE T-ITS · Beijing Institute of Technology · Fakultät Verkehrswissenschaften "Friedrich List" · +2
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  9. 2021
    Lifelong Vehicle Trajectory Prediction Framework Based on Generative ReplayPeng Bao, Zonghai Chen, Jikai Wang … Hao ZhaoIEEE T-ITS · University of Science and Technology of China
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  10. 2022
    Few-Shot Class-Incremental Learning via Compact and Separable Features for Fine-Grained Vehicle RecognitionDe-Wang Li, Hua HuangIEEE T-ITS · Beijing Institute of Technology · Beijing Normal University
  11. 2022
    Real-Time Prediction System of Train Carriage Load Based on Multi-Stream Fuzzy LearningHang Yu, Jie Lü, Anjin Liu … Guangquan ZhangIEEE T-ITS · University of Technology Sydney
  12. 2021
    AdaPool: A Diurnal-Adaptive Fleet Management Framework Using Model-Free Deep Reinforcement Learning and Change Point DetectionMarina Haliem, Vaneet Aggarwal, Bharat BhargavaIEEE T-ITS · Purdue University West Lafayette
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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.