mlsanityData to 7 Oct 2026

Complex Embeddings for Simple Link Prediction

arXiv 1606.06357 ↗First posted 20 Jun 2016cs.AI cs.LG stat.MLcited by 897

Not on the map. Why?

Cited by 34 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In statistical relational learning, the link prediction problem is key to automatically understand the structure of large knowledge bases. As in previous studies, we propose to solve this problem through latent factorization. However, here we make use of complex valued embeddings. The composition of complex embeddings can handle a large variety of binary relations, among them symmetric and antisymmetric relations. Compared to state-of-the-art models such as Neural Tensor Network and Holographic Embeddings, our approach based on complex embeddings is arguably simpler, as it only uses the Hermitian dot product, the complex counterpart of the standard dot product between real vectors. Our approach is scalable to large datasets as it remains linear in both space and time, while consistently outperforming alternative approaches on standard link prediction benchmarks.

Key facts. Cited by 897 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Jun 2016.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 160; 2022: 179; 2023: 183; 2024: 164; 2025: 116; 2026: 95.

897 papers.

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  1. 2021OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphscited by 328
  2. 2021Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Predictioncited by 273
  3. 2022Deep Bidirectional Language-Knowledge Graph Pretrainingcited by 156
  4. 2024GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoningcited by 128
  5. 2021Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learningcited by 106
  6. 2022A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodalcited by 106
  7. 2023Graph Foundation Models: Concepts, Opportunities and Challengescited by 101
  8. 2021Question Answering Over Temporal Knowledge Graphscited by 99
  9. 2022SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Modelscited by 90
  10. 2022Graph Neural Networks for Link Prediction with Subgraph Sketchingcited by 81
  11. 2021Graph Representation Learning in Biomedicinecited by 79
  12. 2021ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphscited by 78
38 more
  1. 2022When Do Flat Minima Optimizers Work?cited by 78
  2. 2022Sequence-to-Sequence Knowledge Graph Completion and Question Answeringcited by 75
  3. 2021From Statistical Relational to Neurosymbolic Artificial Intelligence: a Surveycited by 72
  4. 2022Simple and Efficient Heterogeneous Graph Neural Networkcited by 71
  5. 2023Knowledge Graphs: Opportunities and Challengescited by 70
  6. 2021TimeTraveler: Reinforcement Learning for Temporal Knowledge Graph Forecastingcited by 67
  7. 2021TransferNet: An Effective and Transparent Framework for Multi-hop Question Answering over Relation Graphcited by 60
  8. 2022Neural-Symbolic Models for Logical Queries on Knowledge Graphscited by 60
  9. 2021TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge Graphscited by 59
  10. 2021Complex Knowledge Base Question Answering: A Surveycited by 52
  11. 2022A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphscited by 49
  12. 2023Making Large Language Models Perform Better in Knowledge Graph Completioncited by 48
  13. 2022RHO (ρ): Reducing Hallucination in Open-domain Dialogues with Knowledge Groundingcited by 47
  14. 2021Differentially Private Federated Knowledge Graphs Embeddingcited by 45
  15. 2022From Discrimination to Generation: Knowledge Graph Completion with Generative Transformercited by 45
  16. 2022TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discoverycited by 45
  17. 2022Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completioncited by 44
  18. 2022TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations at Twittercited by 44
  19. 2022Knowledge Graph Contrastive Learning Based on Relation-Symmetrical Structurecited by 43
  20. 2022Temporal Knowledge Graph Reasoning with Historical Contrastive Learningcited by 42
  21. 2022Knowledge Graph Embedding: A Survey from the Perspective of Representation Spacescited by 41
  22. 2022T2G-Former: Organizing Tabular Features into Relation Graphs Promotes Heterogeneous Feature Interactioncited by 41
  23. 2021Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphscited by 39
  24. 2021A Survey on Neural-symbolic Learning Systemscited by 39
  25. 2022Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queriescited by 39
  26. 2022Linkless Link Prediction via Relational Distillationcited by 39
  27. 2023Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearningcited by 39
  28. 2021Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Conescited by 38
  29. 2022OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphscited by 38
  30. 2021A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspectivecited by 37
  31. 2021Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Conceptscited by 37
  32. 2021Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representationscited by 37
  33. 2024KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completioncited by 36
  34. 2024Knowledge Graph Large Language Model (KG-LLM) for Link Predictioncited by 36
  35. 2022On Transforming Reinforcement Learning by Transformer: The Development Trajectorycited by 35
  36. 2023Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databasescited by 35
  37. 2021ChronoR: Rotation Based Temporal Knowledge Graph Embeddingcited by 34
  38. 2021Temporal Knowledge Graph Completion using Box Embeddingscited by 34

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