{"total":45,"rows":[{"id":"2210.15889","title":"Towards Data-and Knowledge-Driven Artificial Intelligence: A Survey on Neuro-Symbolic Computing","created":"2022-10-28","cited_by_count":35,"area":null},{"id":"2309.01038","title":"Neurosymbolic Reinforcement Learning and Planning: A Survey","created":"2023-09-02","cited_by_count":24,"area":null},{"id":"2401.01040","title":"Towards Cognitive AI Systems: a Survey and Prospective on Neuro-Symbolic AI","created":"2024-01-02","cited_by_count":24,"area":null},{"id":"2309.08395","title":"Learning by Self-Explaining","created":"2023-09-15","cited_by_count":17,"area":null},{"id":"2110.01834","title":"Thinking Fast and Slow in AI: the Role of Metacognition","created":"2021-10-05","cited_by_count":11,"area":null},{"id":"2402.07776","title":"TELLER: A Trustworthy Framework for Explainable, Generalizable and Controllable Fake News Detection","created":"2024-02-12","cited_by_count":10,"area":null},{"id":"2306.08057","title":"Symbolic Regression via Control Variable Genetic Programming","created":"2023-05-25","cited_by_count":9,"area":null},{"id":"2310.00637","title":"Knowledge Engineering using Large Language Models","created":"2023-10-01","cited_by_count":9,"area":null},{"id":"2409.13153","title":"Towards Efficient Neuro-Symbolic AI: From Workload Characterization to Hardware Architecture","created":"2024-09-20","cited_by_count":7,"area":null},{"id":"2201.07763","title":"When Is It Acceptable to Break the Rules? Knowledge Representation of Moral Judgement Based on Empirical Data","created":"2022-01-19","cited_by_count":5,"area":null},{"id":"2303.15113","title":"Describing and Organizing Semantic Web and Machine Learning Systems in the SWeMLS-KG","created":"2023-03-27","cited_by_count":5,"area":null},{"id":"2406.12644","title":"Hierarchical Prompting Taxonomy: A Universal Evaluation Framework for Large Language Models Aligned with Human Cognitive Principles","created":"2024-06-18","cited_by_count":5,"area":null},{"id":"2205.04139","title":"The Roles and Modes of Human Interactions with Automated Machine Learning Systems","created":"2022-05-09","cited_by_count":4,"area":null},{"id":"2208.08056","title":"Sampling Through the Lens of Sequential Decision Making","created":"2022-08-17","cited_by_count":4,"area":null},{"id":"2404.15166","title":"Pixels and Predictions: Potential of GPT-4V in Meteorological Imagery Analysis and Forecast Communication","created":"2024-04-22","cited_by_count":4,"area":null},{"id":"2302.02093","title":"Knowledge-enhanced Neural Machine Reasoning: A Review","created":"2023-02-04","cited_by_count":3,"area":null},{"id":"2303.04283","title":"Fast and Slow Planning","created":"2023-03-07","cited_by_count":3,"area":null},{"id":"2404.09877","title":"Synergising Human-like Responses and Machine Intelligence for Planning in Disaster Response","created":"2024-04-15","cited_by_count":3,"area":null},{"id":"2406.11563","title":"Intersymbolic AI: Interlinking Symbolic AI and Subsymbolic AI","created":"2024-06-17","cited_by_count":3,"area":null},{"id":"2508.21550","title":"EZ-Sort: Efficient Pairwise Comparison via Zero-Shot CLIP-Based Pre-Ordering and Human-in-the-Loop Sorting","created":"2025-08-29","cited_by_count":3,"area":null},{"id":"2512.24100","title":"Think Before You Move: Latent Motion Reasoning for Text-to-Motion Generation","created":"2025-12-30","cited_by_count":3,"area":null},{"id":"2101.06644","title":"HySTER: A Hybrid Spatio-Temporal Event Reasoner","created":"2021-01-17","cited_by_count":2,"area":null},{"id":"2308.03990","title":"NEOLAF, an LLM-powered neural-symbolic cognitive architecture","created":"2023-08-08","cited_by_count":2,"area":null},{"id":"2310.19503","title":"Trust, Accountability, and Autonomy in Knowledge Graph-based AI for Self-determination","created":"2023-10-30","cited_by_count":2,"area":null},{"id":"2401.13408","title":"Toward A Causal Framework for Modeling Perception","created":"2024-01-24","cited_by_count":2,"area":null},{"id":"2503.06138","title":"System 0/1/2/3: Quad-process theory for multi-timescale embodied collective cognitive systems","created":"2025-03-08","cited_by_count":2,"area":null},{"id":"2505.24012","title":"Large Language Model Meets Constraint Propagation","created":"2025-05-29","cited_by_count":2,"area":null},{"id":"2509.07122","title":"Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis","created":"2025-09-08","cited_by_count":2,"area":null},{"id":"2109.08301","title":"Comprehensive Multi-Agent Epistemic Planning","created":"2021-09-17","cited_by_count":1,"area":null},{"id":"2205.06483","title":"Modeling Human Behavior Part II -- Cognitive approaches and Uncertainty","created":"2022-05-13","cited_by_count":1,"area":null},{"id":"2307.07628","title":"Value-based Fast and Slow AI Nudging","created":"2023-07-14","cited_by_count":1,"area":null},{"id":"2312.11955","title":"Vertical Symbolic Regression","created":"2023-12-19","cited_by_count":1,"area":null},{"id":"2403.14796","title":"Planning and Acting While the Clock Ticks","created":"2024-03-21","cited_by_count":1,"area":null},{"id":"2412.01752","title":"A Neurosymbolic Fast and Slow Architecture for Graph Coloring","created":"2024-12-02","cited_by_count":1,"area":null},{"id":"2501.17507","title":"Reflections on \"Can AI Understand Our Universe?\"","created":"2025-01-29","cited_by_count":1,"area":null},{"id":"2504.11200","title":"Mutual Understanding between People and Systems via Neurosymbolic AI and Knowledge Graphs","created":"2025-04-15","cited_by_count":1,"area":null},{"id":"2504.19323","title":"NSFlow: An End-to-End FPGA Framework with Scalable Dataflow Architecture for Neuro-Symbolic AI","created":"2025-04-27","cited_by_count":1,"area":null},{"id":"2506.14843","title":"CACTUS as a Reliable Tool for Early Classification of Age-related Macular Degeneration","created":"2025-06-16","cited_by_count":1,"area":null},{"id":"2512.06933","title":"TxSum: User-Centered Ethereum Transaction Understanding with Micro-Level Semantic Grounding","created":"2025-12-07","cited_by_count":1,"area":null},{"id":"2204.14255","title":"Human-in-the-loop online multi-agent approach to increase trustworthiness in ML models through trust scores and data augmentation","created":"2022-04-29","cited_by_count":0,"area":null},{"id":"2205.07862","title":"A Safety Assurable Human-Inspired Perception Architecture","created":"2022-05-10","cited_by_count":0,"area":null},{"id":"2305.09535","title":"What's the Problem, Linda? The Conjunction Fallacy as a Fairness Problem","created":"2023-05-16","cited_by_count":0,"area":null},{"id":"2410.07866","title":"System 2 Reasoning for Human-AI Alignment: Generality and Adaptivity via ARC-AGI","created":"2024-10-10","cited_by_count":0,"area":null},{"id":"2610.06985","title":"CrystalJev: calibrated foundation-model probabilities decide what to compute next in materials discovery","created":"2026-10-04","cited_by_count":0,"area":null},{"id":"2610.14112","title":"Does System One Transfer? Calibrated Typed-Decision Models, Label Budgets, and Translation for Indonesian Regional Languages","created":"2026-10-09","cited_by_count":0,"area":null}],"next_cursor":null}