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Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs

arXiv 1909.01515 ↗First posted 4 Sep 2019cs.CL stat.MLcited by 73

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Abstract (arXiv)

Link prediction is an important way to complete knowledge graphs (KGs), while embedding-based methods, effective for link prediction in KGs, perform poorly on relations that only have a few associative triples. In this work, we propose a Meta Relational Learning (MetaR) framework to do the common but challenging few-shot link prediction in KGs, namely predicting new triples about a relation by only observing a few associative triples. We solve few-shot link prediction by focusing on transferring relation-specific meta information to make model learn the most important knowledge and learn faster, corresponding to relation meta and gradient meta respectively in MetaR. Empirically, our model achieves state-of-the-art results on few-shot link prediction KG benchmarks.

Key facts. Cited by 73 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Sep 2019.

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Citing papers per year: 2021: 13; 2022: 17; 2023: 21; 2024: 11; 2025: 10; 2026: 1.

73 papers.

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  1. 2023PRODIGY: Enabling In-context Learning Over Graphscited by 97
  2. 2023Towards Foundation Models for Knowledge Graph Reasoningcited by 83
  3. 2021NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphscited by 71
  4. 2021OntoZSL: Ontology-enhanced Zero-shot Learningcited by 45
  5. 2024KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completioncited by 36
  6. 2021Relational Learning with Gated and Attentive Neighbor Aggregator for Few-Shot Knowledge Graph Completioncited by 32
  7. 2022Knowledge Is Flat: A Seq2Seq Generative Framework for Various Knowledge Graph Completioncited by 32
  8. 2021Meta-Knowledge Transfer for Inductive Knowledge Graph Embeddingcited by 31
  9. 2021Continual Mixed-Language Pre-Training for Extremely Low-Resource Neural Machine Translationcited by 29
  10. 2022Meta Learning for Natural Language Processing: A Surveycited by 26
  11. 2022Graph Few-shot Learning with Task-specific Structurescited by 26
  12. 2023APPLeNet: Visual Attention Parameterized Prompt Learning for Few-Shot Remote Sensing Image Generalization using CLIPcited by 24
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  1. 2024RAGraph: A General Retrieval-Augmented Graph Learning Frameworkcited by 24
  2. 2021Zero-shot and Few-shot Learning with Knowledge Graphs: A Comprehensive Surveycited by 23
  3. 2022The Neural Process Family: Survey, Applications and Perspectivescited by 23
  4. 2023A Multi-Task Perspective for Link Prediction with New Relation Types and Nodescited by 23
  5. 2022Decomposed Meta-Learning for Few-Shot Named Entity Recognitioncited by 22
  6. 2022Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphscited by 21
  7. 2023Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation Typescited by 21
  8. 2023Neurosymbolic AI for Reasoning over Knowledge Graphs: A Surveycited by 21
  9. 2022Cross-Domain Few-Shot Graph Classificationcited by 19
  10. 2023Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completioncited by 19
  11. 2022Few-shot Relational Reasoning via Connection Subgraph Pretrainingcited by 18
  12. 2024MKGL: Mastery of a Three-Word Languagecited by 17
  13. 2022Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Settingcited by 15
  14. 2023A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directionscited by 15
  15. 2021Multilingual and cross-lingual document classification: A meta-learning approachcited by 14
  16. 2023Generalizing to Unseen Elements: A Survey on Knowledge Extrapolation for Knowledge Graphscited by 14
  17. 2021Trans4E: Link Prediction on Scholarly Knowledge Graphscited by 13
  18. 2022Few-Shot Learning on Graphscited by 11
  19. 2021What Can Knowledge Bring to Machine Learning? -- A Survey of Low-shot Learning for Structured Datacited by 10
  20. 2021Subgraph-aware Few-Shot Inductive Link Prediction via Meta-Learningcited by 9
  21. 2023SARF: Aliasing Relation Assisted Self-Supervised Learning for Few-shot Relation Reasoningcited by 9
  22. 2023On the Evolution of Knowledge Graphs: A Survey and Perspectivecited by 9
  23. 2021Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphscited by 8
  24. 2022Few-Shot Inductive Learning on Temporal Knowledge Graphs using Concept-Aware Informationcited by 8
  25. 2021Meta-Learning with Graph Neural Networks: Methods and Applicationscited by 7
  26. 2021Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learningcited by 6
  27. 2022Learning Meta Representations of One-shot Relations for Temporal Knowledge Graph Link Predictioncited by 6
  28. 2022Hierarchical Relational Learning for Few-Shot Knowledge Graph Completioncited by 6
  29. 2023A Survey On Few-shot Knowledge Graph Completion with Structural and Commonsense Knowledgecited by 6
  30. 2024Large Language Model Enhanced Knowledge Representation Learning: A Surveycited by 6
  31. 2023Hyperbolic Graph Neural Networks at Scale: A Meta Learning Approachcited by 5
  32. 2024A Survey of Few-Shot Learning on Graphs: from Meta-Learning to Pre-Training and Prompt Learningcited by 5
  33. 2022Graph Learning and Its Advancements on Large Language Models: A Holistic Surveycited by 4
  34. 2023Towards Few-shot Inductive Link Prediction on Knowledge Graphs: A Relational Anonymous Walk-guided Neural Process Approachcited by 4
  35. 2025A Survey of Link Prediction in N-ary Knowledge Graphscited by 4
  36. 2024Few-shot Knowledge Graph Relational Reasoning via Subgraph Adaptationcited by 3
  37. 2024Context-Aware Adapter Tuning for Few-Shot Relation Learning in Knowledge Graphscited by 3
  38. 2025TransNet: Transfer Knowledge for Few-shot Knowledge Graph Completioncited by 3

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