mlsanityData to 14 Oct 2026

Neural-Symbolic Learning and Reasoning: A Survey and Interpretation

arXiv 1711.03902 ↗First posted 10 Nov 2017cs.AIcited by 196

Not on the map. Why?

Cited by 37 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

The study and understanding of human behaviour is relevant to computer science, artificial intelligence, neural computation, cognitive science, philosophy, psychology, and several other areas. Presupposing cognition as basis of behaviour, among the most prominent tools in the modelling of behaviour are computational-logic systems, connectionist models of cognition, and models of uncertainty. Recent studies in cognitive science, artificial intelligence, and psychology have produced a number of cognitive models of reasoning, learning, and language that are underpinned by computation. In addition, efforts in computer science research have led to the development of cognitive computational systems integrating machine learning and automated reasoning. Such systems have shown promise in a range of applications, including computational biology, fault diagnosis, training and assessment in simulators, and software verification. This joint survey reviews the personal ideas and views of several researchers on neural-symbolic learning and reasoning. The article is organised in three parts: Firstly, we frame the scope and goals of neural-symbolic computation and have a look at the theoretical foundations. We then proceed to describe the realisations of neural-symbolic computation, systems, and applications. Finally we present the challenges facing the area and avenues for further research.

Key facts. Cited by 196 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Nov 2017.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 26; 2022: 24; 2023: 37; 2024: 36; 2025: 44; 2026: 29.

196 papers.

Sort:

By area:

  1. 2022Generative Flow Networks for Discrete Probabilistic Modelingcited by 114
  2. 2023Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcutscited by 63
  3. 2025Efficient Inference for Large Reasoning Models: A Surveycited by 61
  4. 2021Incorporating Domain Knowledge into Deep Neural Networkscited by 56
  5. 2021Automated Fact-Checking: A Surveycited by 55
  6. 2021Neuro-Symbolic Artificial Intelligence: Current Trendscited by 54
  7. 2021Logic-Driven Context Extension and Data Augmentation for Logical Reasoning of Textcited by 46
  8. 2022Reasoning Like Program Executorscited by 45
  9. 2022Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extractioncited by 44
  10. 2021From LSAT: The Progress and Challenges of Complex Reasoningcited by 43
  11. 2021A Survey on Neural-symbolic Learning Systemscited by 39
  12. 2022Is Neuro-Symbolic AI Meeting its Promise in Natural Language Processing? A Structured Reviewcited by 38
38 more
  1. 2022Deep Learning Methods for Abstract Visual Reasoning: A Survey on Raven's Progressive Matricescited by 37
  2. 2024BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcutscited by 37
  3. 2022Towards Data-and Knowledge-Driven Artificial Intelligence: A Survey on Neuro-Symbolic Computingcited by 35
  4. 2022NeuPSL: Neural Probabilistic Soft Logiccited by 34
  5. 2025Think or Not? Exploring Thinking Efficiency in Large Reasoning Models via an Information-Theoretic Lenscited by 34
  6. 2022A Review of Emerging Research Directions in Abstract Visual Reasoningcited by 33
  7. 2022VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programmingcited by 31
  8. 2021EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use casecited by 30
  9. 2024Logically Consistent Language Models via Neuro-Symbolic Integrationcited by 30
  10. 2023Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentationcited by 29
  11. 2023Neural Probabilistic Logic Programming in Discrete-Continuous Domainscited by 25
  12. 2023Neurosymbolic Reinforcement Learning and Planning: A Surveycited by 24
  13. 2024Towards Cognitive AI Systems: a Survey and Prospective on Neuro-Symbolic AIcited by 24
  14. 2021ProTo: Program-Guided Transformer for Program-Guided Taskscited by 21
  15. 2022Deep Symbolic Learning: Discovering Symbols and Rules from Perceptionscited by 21
  16. 2024A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcutscited by 19
  17. 2021Differentiable Logic Machinescited by 18
  18. 2024Interpretable Concept-Based Memory Reasoningcited by 17
  19. 2024SymbolicAI: A framework for logic-based approaches combining generative models and solverscited by 16
  20. 2024Softened Symbol Grounding for Neuro-symbolic Systemscited by 16
  21. 2024Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomycited by 16
  22. 2021FF-NSL: Feed-Forward Neural-Symbolic Learnercited by 15
  23. 2021Towards Socially Intelligent Agents with Mental State Transition and Human Utilitycited by 14
  24. 2023Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trickcited by 14
  25. 2022Neuro-Symbolic Learning of Answer Set Programs from Raw Datacited by 12
  26. 2023Injecting Logical Constraints into Neural Networks via Straight-Through Estimatorscited by 12
  27. 2024The Role of Foundation Models in Neuro-Symbolic Learning and Reasoningcited by 12
  28. 2022Beyond Object Recognition: A New Benchmark towards Object Concept Learningcited by 11
  29. 2025A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfactioncited by 11
  30. 2021Faster-LTN: a neuro-symbolic, end-to-end object detection architecturecited by 10
  31. 2022Knowledge-augmented Deep Learning and Its Applications: A Surveycited by 10
  32. 2023Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeatcited by 10
  33. 2023Exploiting Code Symmetries for Learning Program Semanticscited by 10
  34. 2024A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligencecited by 10
  35. 2024Weakly Supervised Anomaly Detection via Knowledge-Data Alignmentcited by 10
  36. 2026Incantation: Natural Language as the Action Interface for Multi-Entity Video World Modelscited by 10
  37. 2021pix2rule: End-to-end Neuro-symbolic Rule Learningcited by 9
  38. 2022Tractable Boolean and Arithmetic Circuitscited by 9

50 most cited of 196 All 196 (JSON)