mlsanityData to 7 Oct 2026

Neurosymbolic AI: The 3rd Wave

arXiv 2012.05876 ↗First posted 10 Dec 2020cs.AI cs.LGcited by 253

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Cited by 38 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Current advances in Artificial Intelligence (AI) and Machine Learning (ML) have achieved unprecedented impact across research communities and industry. Nevertheless, concerns about trust, safety, interpretability and accountability of AI were raised by influential thinkers. Many have identified the need for well-founded knowledge representation and reasoning to be integrated with deep learning and for sound explainability. Neural-symbolic computing has been an active area of research for many years seeking to bring together robust learning in neural networks with reasoning and explainability via symbolic representations for network models. In this paper, we relate recent and early research results in neurosymbolic AI with the objective of identifying the key ingredients of the next wave of AI systems. We focus on research that integrates in a principled way neural network-based learning with symbolic knowledge representation and logical reasoning. The insights provided by 20 years of neural-symbolic computing are shown to shed new light onto the increasingly prominent role of trust, safety, interpretability and accountability of AI. We also identify promising directions and challenges for the next decade of AI research from the perspective of neural-symbolic systems.

Key facts. Cited by 253 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Dec 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 24; 2022: 33; 2023: 34; 2024: 34; 2025: 55; 2026: 73.

253 papers.

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  1. 2023Large Language Modelscited by 774
  2. 2022PAL: Program-aided Language Modelscited by 635
  3. 2022Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoningcited by 331
  4. 2021D'ya like DAGs? A Survey on Structure Learning and Causal Discoverycited by 209
  5. 2023SatLM: Satisfiability-Aided Language Models Using Declarative Promptingcited by 100
  6. 2021Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoningcited by 85
  7. 2021A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challengescited by 68
  8. 2022LAMBADA: Backward Chaining for Automated Reasoning in Natural Languagecited by 66
  9. 2023Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolationcited by 56
  10. 2021Inductive logic programming at 30cited by 46
  11. 2021Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use casescited by 39
  12. 2021A Survey on Neural-symbolic Learning Systemscited by 39
38 more
  1. 2022Deep Learning Methods for Abstract Visual Reasoning: A Survey on Raven's Progressive Matricescited by 37
  2. 2022Is Neuro-Symbolic AI Meeting its Promise in Natural Language Processing? A Structured Reviewcited by 37
  3. 2021Tell me why! Explanations support learning relational and causal structurecited by 36
  4. 2025Neuro-Symbolic AI in 2024: A Systematic Reviewcited by 36
  5. 2022Towards Data-and Knowledge-Driven Artificial Intelligence: A Survey on Neuro-Symbolic Computingcited by 34
  6. 2023Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logiccited by 34
  7. 2024Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6Gcited by 30
  8. 2024How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Datacited by 29
  9. 2021Symbolic Behaviour in Artificial Intelligencecited by 24
  10. 2021Techniques for Symbol Grounding with SATNetcited by 24
  11. 2023Neurosymbolic Reinforcement Learning and Planning: A Surveycited by 24
  12. 2021Neuro-Symbolic Hierarchical Rule Inductioncited by 23
  13. 2022Neuro-Symbolic Verification of Deep Neural Networkscited by 21
  14. 2023Neurosymbolic AI for Reasoning over Knowledge Graphs: A Surveycited by 21
  15. 2022Neuro-Symbolic Causal Reasoning Meets Signaling Game for Emergent Semantic Communicationscited by 20
  16. 2025Beyond the convexity assumption: Realistic tabular data generation under quantifier-free real linear constraintscited by 18
  17. 2024Concept-Based Explanations in Computer Vision: Where Are We and Where Could We Go?cited by 17
  18. 2022On the link between conscious function and general intelligence in humans and machinescited by 15
  19. 2024SymbolicAI: A framework for logic-based approaches combining generative models and solverscited by 15
  20. 2023Scalable Neural-Probabilistic Answer Set Programmingcited by 14
  21. 2023Learning Differentiable Logic Programs for Abstract Visual Reasoningcited by 12
  22. 2023Do Deep Neural Networks Capture Compositionality in Arithmetic Reasoning?cited by 11
  23. 2023A Framework for Neurosymbolic Robot Action Planning using Large Language Modelscited by 11
  24. 2022Neuro-Symbolic Artificial Intelligence (AI) for Intent based Semantic Communicationcited by 10
  25. 2024A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligencecited by 10
  26. 2021Automating Crystal-Structure Phase Mapping: Combining Deep Learning with Constraint Reasoningcited by 9
  27. 2022Tractable Boolean and Arithmetic Circuitscited by 9
  28. 2024Metacognitive AI: Framework and the Case for a Neurosymbolic Approachcited by 9
  29. 2021The General Theory of General Intelligence: A Pragmatic Patternist Perspectivecited by 8
  30. 2021SLASH: Embracing Probabilistic Circuits into Neural Answer Set Programmingcited by 8
  31. 2023V-LoL: A Diagnostic Dataset for Visual Logical Learningcited by 8
  32. 2024Comprehensible Artificial Intelligence on Knowledge Graphs: A surveycited by 8
  33. 2024DeepDFA: Automata Learning through Neural Probabilistic Relaxationscited by 8
  34. 2025VLN-Zero: Rapid Exploration and Cache-Enabled Neurosymbolic Vision-Language Planning for Zero-Shot Transfer in Robot Navigationcited by 8
  35. 2021A Critical Review of Inductive Logic Programming Techniques for Explainable AIcited by 7
  36. 2022Knowledge Management System with NLP-Assisted Annotations: A Brief Survey and Outlookcited by 7
  37. 2022Neuro-Symbolic Learning: Principles and Applications in Ophthalmologycited by 7
  38. 2022CoRRPUS: Code-based Structured Prompting for Neurosymbolic Story Understandingcited by 7

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