mlsanityData to 14 Oct 2026

Continual Learning on Graphs: A Survey

arXiv 2402.06330 ↗First posted 9 Feb 2024cs.LGcited by 12

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Abstract (arXiv)

Recently, continual graph learning has been increasingly adopted for diverse graph-structured data processing tasks in non-stationary environments. Despite its promising learning capability, current studies on continual graph learning mainly focus on mitigating the catastrophic forgetting problem while ignoring continuous performance improvement. To bridge this gap, this article aims to provide a comprehensive survey of recent efforts on continual graph learning. Specifically, we introduce a new taxonomy of continual graph learning from the perspective of overcoming catastrophic forgetting. Moreover, we systematically analyze the challenges of applying these continual graph learning methods in improving performance continuously and then discuss the possible solutions. Finally, we present open issues and future directions pertaining to the development of continual graph learning and discuss how they impact continuous performance improvement.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 120 of its 165 references that are in the map. First posted on arXiv 9 Feb 2024.

Builds on

120 of 165 references.

References · 120

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38 more
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50 most cited of 120 All 120 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 4; 2025: 5; 2026: 3.

12 papers.

  1. 2024Towards Lifelong Learning of Large Language Models: A Surveycited by 64
  2. 2024A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptationcited by 17
  3. 2024Replay-and-Forget-Free Graph Class-Incremental Learning: A Task Profiling and Prompting Approachcited by 12
  4. 2024Graph Memory Learning: Imitating Lifelong Remembering and Forgetting of Brain Networkscited by 4
  5. 2025Online Continual Graph Learningcited by 3
  6. 2025A Selective Learning Method for Temporal Graph Continual Learningcited by 1
  7. 2025PROL : Rehearsal Free Continual Learning in Streaming Data via Prompt Online Learningcited by 1
  8. 2025AL-GNN: Privacy-Preserving and Replay-Free Continual Graph Learning via Analytic Learningcited by 1
  9. 2026TAAM:Inductive Graph-Class Incremental Learning with Task-Aware Adaptive Modulationcited by 1
  10. 2025Task-Aware Adaptive Modulation: A Replay-Free and Resource-Efficient Approach For Continual Graph Learningcited by 0
  11. 2026Continual Learning for fMRI-Based Brain Disorder Diagnosis via Functional Connectivity Matrices Generative Replaycited by 0
  12. 2026HiTS-CL: A Continual Learning Framework for Long-Horizon Temporal Knowledge Graph Extrapolationcited by 0