mlsanityData to 7 Oct 2026

Neuro-Symbolic AI in 2024: A Systematic Review

arXiv 2501.05435 ↗First posted 9 Jan 2025cs.AIcited by 36

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Abstract (arXiv)

Background: The field of Artificial Intelligence has undergone cyclical periods of growth and decline, known as AI summers and winters. Currently, we are in the third AI summer, characterized by significant advancements and commercialization, particularly in the integration of Symbolic AI and Sub-Symbolic AI, leading to the emergence of Neuro-Symbolic AI. Methods: The review followed the PRISMA methodology, utilizing databases such as IEEE Explore, Google Scholar, arXiv, ACM, and SpringerLink. The inclusion criteria targeted peer-reviewed papers published between 2020 and 2024. Papers were screened for relevance to Neuro-Symbolic AI, with further inclusion based on the availability of associated codebases to ensure reproducibility. Results: From an initial pool of 1,428 papers, 167 met the inclusion criteria and were analyzed in detail. The majority of research efforts are concentrated in the areas of learning and inference (63%), logic and reasoning (35%), and knowledge representation (44%). Explainability and trustworthiness are less represented (28%), with Meta-Cognition being the least explored area (5%). The review identifies significant interdisciplinary opportunities, particularly in integrating explainability and trustworthiness with other research areas. Conclusion: Neuro-Symbolic AI research has seen rapid growth since 2020, with concentrated efforts in learning and inference. Significant gaps remain in explainability, trustworthiness, and Meta-Cognition. Addressing these gaps through interdisciplinary research will be crucial for advancing the field towards more intelligent, reliable, and context-aware AI systems.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). Builds on 95 of its 160 references that are in the map. First posted on arXiv 9 Jan 2025.

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95 of 160 references.

References · 95

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38 more
  1. 2023LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Proverscited by 161
  2. 2022Semantic Probabilistic Layers for Neuro-Symbolic Learningcited by 103
  3. 2022Do Androids Laugh at Electric Sheep? Humor "Understanding" Benchmarks from The New Yorker Caption Contestcited by 98
  4. 2020Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanationscited by 94
  5. 2020GLUCOSE: GeneraLized and COntextualized Story Explanationscited by 85
  6. 2020A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events Portalcited by 72
  7. 2021From Statistical Relational to Neurosymbolic Artificial Intelligence: a Surveycited by 72
  8. 2023Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcutscited by 63
  9. 2023NS3D: Neuro-Symbolic Grounding of 3D Objects and Relationscited by 57
  10. 2022Learning Neuro-Symbolic Skills for Bilevel Planningcited by 55
  11. 2022Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasetscited by 54
  12. 2020Leveraging Abstract Meaning Representation for Knowledge Base Question Answeringcited by 53
  13. 2022A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inferencecited by 50
  14. 2022FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive Summarizationcited by 49
  15. 2021Abstract Spatial-Temporal Reasoning via Probabilistic Abduction and Executioncited by 43
  16. 2021Learning Neuro-Symbolic Relational Transition Models for Bilevel Planningcited by 43
  17. 2022FactGraph: Evaluating Factuality in Summarization with Semantic Graph Representationscited by 41
  18. 2021A Survey on Neural-symbolic Learning Systemscited by 39
  19. 2022QALD-9-plus: A Multilingual Dataset for Question Answering over DBpedia and Wikidata Translated by Native Speakerscited by 39
  20. 2020Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselinescited by 37
  21. 2021Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphscited by 36
  22. 2024BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcutscited by 36
  23. 2021Analyzing Commonsense Emergence in Few-shot Knowledge Modelscited by 34
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  26. 2022JARVIS: A Neuro-Symbolic Commonsense Reasoning Framework for Conversational Embodied Agentscited by 29
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  36. 2023Towards a Unified Transformer-based Framework for Scene Graph Generation and Human-object Interaction Detectioncited by 15
  37. 2020Learning Task-General Representations with Generative Neuro-Symbolic Modelingcited by 14
  38. 2021Hierarchical Motion Understanding via Motion Programscited by 14

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Citing papers per year: 2025: 16; 2026: 20.

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  2. 2025The Rise of Small Language Models in Healthcare: A Comprehensive Surveycited by 18
  3. 2025Large Language Models in Bioinformatics: A Surveycited by 6
  4. 2025Towards Transparent AI: A Survey on Explainable Language Modelscited by 3
  5. 2026Egocentric Co-Pilot: Web-Native Smart-Glasses Agents for Assistive Egocentric AIcited by 3
  6. 2026Ontology-Constrained Neural Reasoning in Enterprise Agentic Systems: A Neurosymbolic Architecture for Domain-Grounded AI Agentscited by 3
  7. 2025Foundations of a Developmental Design Paradigm for Integrated Continual Learning, Deliberative Behavior, and Comprehensibilitycited by 2
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  10. 2025On the Parallels Between Evolutionary Theory and the State of AIcited by 1
  11. 2025Follow My Lead: Logical Fallacy Classification with Knowledge-Augmented LLMscited by 1
  12. 2025From Explainability to Action: A Generative Operational Framework for Integrating XAI in Clinical Mental Health Screeningcited by 1
24 more
  1. 2026Autonomous Business System via Neuro-symbolic AIcited by 1
  2. 2026Differentiable Modal Logic for Multi-Agent Diagnosis, Orchestration and Communicationcited by 1
  3. 2026Neuro-Symbolic Strong-AI Robots with Closed Knowledge Assumption: Learning and Deductionscited by 1
  4. 2026A neurosymbolic Approach with Epistemic Deep Learning for Hierarchical Image Classificationcited by 1
  5. 2025Cognitive Silicon: An Architectural Blueprint for Post-Industrial Computing Systemscited by 0
  6. 2025Evolutionary Developmental Biology Can Serve as the Conceptual Foundation for a New Design Paradigm in Artificial Intelligencecited by 0
  7. 2025Model-Grounded Symbolic Artificial Intelligence Systems Learning and Reasoning with Model-Grounded Symbolic Artificial Intelligence Systemscited by 0
  8. 2025HyDRA: A Hybrid-Driven Reasoning Architecture for Verifiable Knowledge Graphscited by 0
  9. 2025Towards Reliable Multi-Agent Systems for Marketing Applications via Reflection, Memory, and Planningcited by 0
  10. 2025PromptGuard at BLP-2025 Task 1: A Few-Shot Classification Framework Using Majority Voting and Keyword Similarity for Bengali Hate Speech Detectioncited by 0
  11. 2025Multi-task GINN-LP for Multi-target Symbolic Regressioncited by 0
  12. 2026Enhancing Vision Language Models with Logic Reasoning for Situational Awarenesscited by 0
  13. 2026SciTaRC: A Plan-Annotated Scientific Tabular QA Benchmark for Language Reasoning and Complex Computationcited by 0
  14. 2026Delta1 with LLM: symbolic and neural integration for credible and explainable reasoningcited by 0
  15. 2026A Neuro-Symbolic System for Interpretable Multimodal Physiological Signals Integration in Human Fatigue Detectioncited by 0
  16. 2026ANDRE: An Attention-based Neuro-symbolic Differentiable Rule Extractor for Inductive Logic Programmingcited by 0
  17. 2026Homoglyph-based Adversarial Perturbation of Introductory Computer Science Theory Problemscited by 0
  18. 2026Neuro-Symbolic Agents for Regulated Process Automation: Challenges and Research Agendacited by 0
  19. 2026The Almost Intelligent Revolution: Options for Scaling Up Deliberation and Empowering People with AIcited by 0
  20. 2026The AI Accountability Ecosystem in the Era of Language Modelscited by 0
  21. 2026On Measuring Semantic Preservation in Legal Ontology Learningcited by 0
  22. 2026A Task-Centric Ontology and Deterministic Domain Rules as a Verifiable Core for AI-Assisted Chemistry Problem Solvingcited by 0
  23. 2026Hallucinations in LLMs: A Lifecycle-Based Survey of Causes, Detection, Mitigation, and Preventioncited by 0
  24. 2026What Can Analogy Tell Us About Artificial Consciousness?cited by 0