mlsanityData to 14 Oct 2026

Neural-Symbolic Reasoning over Knowledge Graphs: A Survey from a Query Perspective

arXiv 2412.10390 ↗First posted 30 Nov 2024cs.AIcited by 20

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

Abstract (arXiv)

Knowledge graph reasoning is pivotal in various domains such as data mining, artificial intelligence, the Web, and social sciences. These knowledge graphs function as comprehensive repositories of human knowledge, facilitating the inference of new information. Traditional symbolic reasoning, despite its strengths, struggles with the challenges posed by incomplete and noisy data within these graphs. In contrast, the rise of Neural Symbolic AI marks a significant advancement, merging the robustness of deep learning with the precision of symbolic reasoning. This integration aims to develop AI systems that are not only highly interpretable and explainable but also versatile, effectively bridging the gap between symbolic and neural methodologies. Additionally, the advent of large language models (LLMs) has opened new frontiers in knowledge graph reasoning, enabling the extraction and synthesis of knowledge in unprecedented ways. This survey offers a thorough review of knowledge graph reasoning, focusing on various query types and the classification of neural symbolic reasoning. Furthermore, it explores the innovative integration of knowledge graph reasoning with large language models, highlighting the potential for groundbreaking advancements. This comprehensive overview is designed to support researchers and practitioners across multiple fields, including data mining, AI, the Web, and social sciences, by providing a detailed understanding of the current landscape and future directions in knowledge graph reasoning.

Key facts. Cited by 20 papers in the map (data through 14 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. Builds on 14 of its 91 references that are in the map. First posted on arXiv 30 Nov 2024.

Builds on

14 of 91 references.

Closest ancestors · 3

Same direction, newest first

  1. 2023KG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language Models17 Oct
  2. 2023Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph15 Jul
  3. 2022GreaseLM: Graph REASoning Enhanced Language Models for Question Answering21 Jan

Other references · 11

  1. 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarizationcited by 1,453
  2. 2014Embedding Entities and Relations for Learning and Inference in Knowledge Basescited by 932
  3. 2019RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Spacecited by 898
  4. 2023REPLUG: Retrieval-Augmented Black-Box Language Modelscited by 792
  5. 2021QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answeringcited by 388
  6. 2017DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoningcited by 266
  7. 2020Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddingscited by 171
  8. 2020RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphscited by 118
  9. 2020Complex Query Answering with Neural Link Predictorscited by 99
  10. 2016TensorLog: A Differentiable Deductive Databasecited by 29
  11. 2023Query2Triple: Unified Query Encoding for Answering Diverse Complex Queries over Knowledge Graphscited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 6; 2026: 14.

20 papers.

Sort:

By area:

  1. 2025Top Ten Challenges Towards Agentic Neural Graph Databasescited by 13
  2. 2025Position: Foundation Models for Tabular Data within Systemic Contexts Need Groundingcited by 6
  3. 2025MIXRAG : Mixture-of-Experts Retrieval-Augmented Generation for Textual Graph Understanding and Question Answeringcited by 6
  4. 2026FinRule-Bench: A Benchmark for Joint Reasoning over Financial Tables and Principlescited by 5
  5. 2025LLMTM: Benchmarking and Optimizing LLMs for Temporal Motif Analysis in Dynamic Graphscited by 4
  6. 2026Multi-hop Reasoning and Retrieval in Embedding Space: Leveraging Large Language Models with Knowledgecited by 2
  7. 2026Neural-Symbolic Logic Query Answering in Non-Euclidean Spacecited by 2
  8. 2026Prompt-tuning with Attribute Guidance for Low-resource Entity Matchingcited by 2
  9. 2025Efficient and Scalable Neural Symbolic Search for Knowledge Graph Complex Query Answeringcited by 1
  10. 2026On the Generalization Gap in LLM Planning: Tests and Verifier-Reward RLcited by 1
  11. 2026Evolving Beyond Snapshots: Harmonizing Structure and Sequence via Entity State Tuning for Temporal Knowledge Graph Forecastingcited by 1
  12. 2026Mixture of Demonstrations for Textual Graph Understanding and Question Answeringcited by 1
8 more
  1. 2025An Automated Theorem Generator with Theoretical Foundation Based on Rectangular Standard Contradictioncited by 0
  2. 2026Panning for Gold: Expanding Domain-Specific Knowledge Graphs with General Knowledgecited by 0
  3. 2026Diagnosing Structural Failures in LLM-Based Evidence Extraction for Meta-Analysiscited by 0
  4. 2026Neural Scalable Symbolic Search Framework for Complex Logical Queries with Multiple Free Variablescited by 0
  5. 2026Outage Detection in Self-Healing Smart Grids Using Reinforcement Learning with Spectral Graph Neural Networkscited by 0
  6. 2026Neurosymbolics for Data Engineering: Achieving Long Context Token Reduction Without Finetuningcited by 0
  7. 2026NeuroGraph: An AI Graph-Driven Neuro-Symbolic Framework for Explainable Threat Reasoning in Advanced Manufacturingcited by 0
  8. 2026Robust Conformal Consensus: Multi-Agent LLM-as-a-Judge Interval Evaluation with Conformal Predictioncited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Neuro-Symbolic Query Optimization in Knowledge Graphs
  2. 2025From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies
  3. 2023Rethinking Language Models as Symbolic Knowledge Graphs
  4. 2025Towards Unified Neurosymbolic Reasoning on Knowledge Graphs
  5. 2023Neurosymbolic AI for Reasoning over Knowledge Graphs: A Survey
  6. 2025Neuro-Symbolic Artificial Intelligence: Towards Improving the Reasoning Abilities of Large Language Models
  7. 2026LLMs+Graphs: Toward Graph-Native, Synergistic AI Systems
  8. 2026Better Later Than Sooner: Neuro-Symbolic Knowledge Graph Construction via Ontology-grounded Post-extraction Correction