mlsanityData to 7 Oct 2026

Neural-Symbolic Models for Logical Queries on Knowledge Graphs

arXiv 2205.10128 ↗First posted 16 May 2022cs.AI cs.LGcited by 60

On the map: LLM reasoning → Knowledge- and tool-augmented reasoning

Abstract (arXiv)

Answering complex first-order logic (FOL) queries on knowledge graphs is a fundamental task for multi-hop reasoning. Traditional symbolic methods traverse a complete knowledge graph to extract the answers, which provides good interpretation for each step. Recent neural methods learn geometric embeddings for complex queries. These methods can generalize to incomplete knowledge graphs, but their reasoning process is hard to interpret. In this paper, we propose Graph Neural Network Query Executor (GNN-QE), a neural-symbolic model that enjoys the advantages of both worlds. GNN-QE decomposes a complex FOL query into relation projections and logical operations over fuzzy sets, which provides interpretability for intermediate variables. To reason about the missing links, GNN-QE adapts a graph neural network from knowledge graph completion to execute the relation projections, and models the logical operations with product fuzzy logic. Experiments on 3 datasets show that GNN-QE significantly improves over previous state-of-the-art models in answering FOL queries. Meanwhile, GNN-QE can predict the number of answers without explicit supervision, and provide visualizations for intermediate variables.

Key facts. Cited by 60 papers in the map (data through 7 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. Builds on 26 of its 44 references that are in the map. First posted on arXiv 16 May 2022.

Builds on

26 of 44 references.

References · 26

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2017Modeling Relational Data with Graph Convolutional Networkscited by 1,684
  3. 2014Embedding Entities and Relations for Learning and Inference in Knowledge Basescited by 929
  4. 2016Complex Embeddings for Simple Link Predictioncited by 897
  5. 2019RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Spacecited by 893
  6. 2020Principal Neighbourhood Aggregation for Graph Netscited by 477
  7. 2019Composition-based Multi-Relational Graph Convolutional Networkscited by 395
  8. 2021Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Predictioncited by 273
  9. 2017DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoningcited by 265
  10. 2015A Review of Relational Machine Learning for Knowledge Graphscited by 264
  11. 2019Inductive Relation Prediction by Subgraph Reasoningcited by 237
  12. 2021Identity-aware Graph Neural Networkscited by 197
14 more
  1. 2019DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphscited by 173
  2. 2020Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddingscited by 169
  3. 2017Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learningcited by 161
  4. 2020Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphscited by 128
  5. 2018Embedding Logical Queries on Knowledge Graphscited by 120
  6. 2020RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphscited by 117
  7. 2020Complex Query Answering with Neural Link Predictorscited by 98
  8. 2021ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphscited by 78
  9. 2015Traversing Knowledge Graphs in Vector Spacecited by 51
  10. 2020Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphscited by 35
  11. 2020LowFER: Low-rank Bilinear Pooling for Link Predictioncited by 20
  12. 2020Reasoning on Knowledge Graphs with Debate Dynamicscited by 16
  13. 2021Learning to Walk with Dual Agents for Knowledge Graph Reasoningcited by 16
  14. 2021Fuzzy Logic Based Logical Query Answering on Knowledge Graphscited by 11

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 7; 2023: 22; 2024: 18; 2025: 8; 2026: 5.

60 papers.

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  1. 2022Binding Language Models in Symbolic Languagescited by 224
  2. 2023Towards Foundation Models for Knowledge Graph Reasoningcited by 83
  3. 2023Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databasescited by 35
  4. 2022Weisfeiler and Leman Go Relationalcited by 28
  5. 2022Answering Complex Logical Queries on Knowledge Graphs via Query Computation Tree Optimizationcited by 28
  6. 2023Logical Message Passing Networks with One-hop Inference on Atomic Formulascited by 28
  7. 2022Inductive Logical Query Answering in Knowledge Graphscited by 25
  8. 2023Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation Typescited by 21
  9. 2023Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraintscited by 21
  10. 2022Neural-Symbolic Entangled Framework for Complex Query Answeringcited by 18
  11. 2023Wasserstein-Fisher-Rao Embedding: Logical Query Embeddings with Local Comparison and Global Transportcited by 16
  12. 2023Adapting Neural Link Predictors for Data-Efficient Complex Query Answeringcited by 13
38 more
  1. 2023Sequential Query Encoding For Complex Query Answering on Knowledge Graphscited by 13
  2. 2023A Review on Knowledge Graphs for Healthcare: Resources, Applications, and Promisescited by 13
  3. 2024A Foundation Model for Zero-shot Logical Query Reasoningcited by 13
  4. 2023Rethinking Language Models as Symbolic Knowledge Graphscited by 12
  5. 2023Knowledge Graph Reasoning over Entities and Numerical Valuescited by 11
  6. 2023Artificial Intelligence for Drug Discovery: Are We There Yet?cited by 11
  7. 2024Neuro-Symbolic AI: Explainability, Challenges, and Future Trendscited by 10
  8. 2022NQE: N-ary Query Embedding for Complex Query Answering over Hyper-Relational Knowledge Graphscited by 9
  9. 2023Adaptive Path-Memory Network for Temporal Knowledge Graph Reasoningcited by 9
  10. 2023Temporal Inductive Path Neural Network for Temporal Knowledge Graph Reasoningcited by 9
  11. 2024Is Complex Query Answering Really Complex?cited by 7
  12. 2023Knowledge-augmented Graph Machine Learning for Drug Discovery: A Surveycited by 6
  13. 2023LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literalscited by 6
  14. 2025Enhancing Transformers for Generalizable First-Order Logical Entailmentcited by 6
  15. 2023Knowledge Graphs Queryingcited by 5
  16. 2023Privacy-Preserved Neural Graph Databasescited by 5
  17. 2024Conditional Logical Message Passing Transformer for Complex Query Answeringcited by 5
  18. 2024Generating SROI^- Ontologies via Knowledge Graph Query Embedding Learningcited by 5
  19. 2023A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphscited by 4
  20. 2023Query2Triple: Unified Query Encoding for Answering Diverse Complex Queries over Knowledge Graphscited by 4
  21. 2024Learning Federated Neural Graph Databases for Answering Complex Queries from Distributed Knowledge Graphscited by 4
  22. 2024DAGE: DAG Query Answering via Relational Combinator with Logical Constraintscited by 4
  23. 2024Improving Multi-hop Logical Reasoning in Knowledge Graphs with Context-Aware Query Representation Learningcited by 3
  24. 2024CrysToGraph: A Comprehensive Predictive Model for Crystal Materials Properties and the Benchmarkcited by 3
  25. 2022TAR: Neural Logical Reasoning across TBox and ABoxcited by 2
  26. 2023Modeling Relational Patterns for Logical Query Answering over Knowledge Graphscited by 2
  27. 2024Extending Complex Logical Queries on Uncertain Knowledge Graphscited by 2
  28. 2024RConE: Rough Cone Embedding for Multi-Hop Logical Query Answering on Multi-Modal Knowledge Graphscited by 2
  29. 2025Enhancing LLM Tool Use with High-quality Instruction Data from Knowledge Graphcited by 2
  30. 2026Neural-Symbolic Logic Query Answering in Non-Euclidean Spacecited by 2
  31. 2023Navigating Healthcare Insights: A Birds Eye View of Explainability with Knowledge Graphscited by 1
  32. 2024SemPool: Simple, robust, and interpretable KG pooling for enhancing language modelscited by 1
  33. 2024Pathformer: Recursive Path Query Encoding for Complex Logical Query Answeringcited by 1
  34. 2024Complex Logical Query Answering by Calibrating Knowledge Graph Completion Modelscited by 1
  35. 2024Edge Contrastive Learning: An Augmentation-Free Graph Contrastive Learning Modelcited by 1
  36. 2025KGCompiler: Deep Learning Compilation Optimization for Knowledge Graph Complex Logical Query Answeringcited by 1
  37. 2025Efficient and Scalable Neural Symbolic Search for Knowledge Graph Complex Query Answeringcited by 1
  38. 2025DeepGraphLog for Layered Neurosymbolic AIcited by 1

50 most cited of 60 All 60 (JSON)

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  1. 2022Neural Methods for Logical Reasoning Over Knowledge Graphs
  2. 2023Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors
  3. 2025A Large Language Model Based Method for Complex Logical Reasoning over Knowledge Graphs
  4. 2026Q-GNN: Query-Conditioned Graph Neural Networks with Type Awareness for Knowledge Graph Completion
  5. 2025Neural-Symbolic Message Passing with Dynamic Pruning
  6. 2022GammaE: Gamma Embeddings for Logical Queries on Knowledge Graphs
  7. 2025Fully Geometric Multi-Hop Reasoning on Knowledge Graphs with Transitive Relations
  8. 2023Query Structure Modeling for Inductive Logical Reasoning Over Knowledge Graphs