mlsanityData to 14 Oct 2026

Graph Domain Adaptation: Challenges, Progress and Prospects

arXiv 2402.00904 ↗First posted 1 Feb 2024cs.LG cs.AIcited by 11

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Abstract (arXiv)

As graph representation learning often suffers from label scarcity problems in real-world applications, researchers have proposed graph domain adaptation (GDA) as an effective knowledge-transfer paradigm across graphs. In particular, to enhance model performance on target graphs with specific tasks, GDA introduces a bunch of task-related graphs as source graphs and adapts the knowledge learnt from source graphs to the target graphs. Since GDA combines the advantages of graph representation learning and domain adaptation, it has become a promising direction of transfer learning on graphs and has attracted an increasing amount of research interest in recent years. In this paper, we comprehensively overview the studies of GDA and present a detailed survey of recent advances. Specifically, we outline the research status and challenges, propose a taxonomy, introduce the details of representative works, and discuss the prospects. To the best of our knowledge, this paper is the first survey for graph domain adaptation. A detailed paper list is available at https://github.com/Skyorca/Awesome-Graph-Domain-Adaptation-Papers.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 26 of its 71 references that are in the map. First posted on arXiv 1 Feb 2024.

Builds on

26 of 71 references.

References · 26

  1. 2019A Comprehensive Survey on Transfer Learningcited by 1,160
  2. 2019Multi-scale Attributed Node Embeddingcited by 548
  3. 2019Semi-supervised Domain Adaptation via Minimax Entropycited by 335
  4. 2019Graph Transfer Learning via Adversarial Domain Adaptation with Graph Convolutioncited by 67
  5. 2020Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptationcited by 64
  6. 2021Few-shot Network Anomaly Detection via Cross-network Meta-learningcited by 64
  7. 2020Learning Disentangled Semantic Representation for Domain Adaptationcited by 55
  8. 2023CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classificationcited by 46
  9. 2023Structural Re-weighting Improves Graph Domain Adaptationcited by 45
  10. 2020Adversarial Deep Network Embedding for Cross-network Node Classificationcited by 44
  11. 2019DANE: Domain Adaptive Network Embeddingcited by 43
  12. 2022Non-IID Transfer Learning on Graphscited by 43
14 more
  1. 2021Graph Domain Adaptation: A Generative Viewcited by 35
  2. 2022Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive Alignmentcited by 31
  3. 2023Semi-supervised Domain Adaptation in Graph Transfer Learningcited by 27
  4. 2018Domain Adaptation on Graphs by Learning Aligned Graph Basescited by 24
  5. 2021Source Free Unsupervised Graph Domain Adaptationcited by 18
  6. 2023Explaining and Adapting Graph Conditional Shiftcited by 14
  7. 2023ALEX: Towards Effective Graph Transfer Learning with Noisy Labelscited by 11
  8. 2023Bridged-GNN: Knowledge Bridge Learning for Effective Knowledge Transfercited by 10
  9. 2023Domain-adaptive Message Passing Graph Neural Networkcited by 10
  10. 2023OpenGDA: Graph Domain Adaptation Benchmark for Cross-network Learningcited by 5
  11. 2023Domain-adaptive Graph Attention-supervised Network for Cross-network Edge Classificationcited by 5
  12. 2023Semi-supervised Domain Adaptation on Graphs with Contrastive Learning and Minimax Entropycited by 4
  13. 2020GDA-HIN: A Generalized Domain Adaptive Model across Heterogeneous Information Networkscited by 1
  14. 2024Population Graph Cross-Network Node Classification for Autism Detection Across Sample Groupscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 5; 2025: 5; 2026: 1.

11 papers.

  1. 2024Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insightscited by 44
  2. 2025On the Benefits of Attribute-Driven Graph Domain Adaptationcited by 19
  3. 2025Homophily Enhanced Graph Domain Adaptationcited by 9
  4. 2024DELTA: Dual Consistency Delving with Topological Uncertainty for Active Graph Domain Adaptationcited by 2
  5. 2024Exploring Graph Mamba: A Comprehensive Survey on State-Space Models for Graph Learningcited by 2
  6. 2025Cross-Domain Graph Anomaly Detection via Test-Time Training with Homophily-Guided Self-Supervisioncited by 2
  7. 2024A Benchmark on Directed Graph Representation Learning in Hardware Designscited by 1
  8. 2025BotTrans: A Multi-Source Graph Domain Adaptation Approach for Social Bot Detectioncited by 1
  9. 2024Domain Adaptive Unfolded Graph Neural Networkscited by 0
  10. 2025Fractal Graph Contrastive Learningcited by 0
  11. 2026Selectivity Matters: Source Node Influence Pruning for Unsupervised Graph Domain Adaptationcited by 0