{"total":21,"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":"2106.13103","title":"FF-NSL: Feed-Forward Neural-Symbolic Learner","created":"2021-06-24","cited_by_count":15,"area":null},{"id":"2304.07063","title":"Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors","created":"2023-04-14","cited_by_count":13,"area":null},{"id":"2312.11522","title":"Assessing SATNet's Ability to Solve the Symbol Grounding Problem","created":"2023-12-13","cited_by_count":10,"area":null},{"id":"2106.07487","title":"pix2rule: End-to-end Neuro-symbolic Rule Learning","created":"2021-06-14","cited_by_count":9,"area":null},{"id":"2405.00532","title":"ULLER: A Unified Language for Learning and Reasoning","created":"2024-05-01","cited_by_count":9,"area":null},{"id":"2209.01397","title":"Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction","created":"2022-09-03","cited_by_count":7,"area":null},{"id":"2211.11281","title":"Intelligent Computing: The Latest Advances, Challenges and Future","created":"2022-11-21","cited_by_count":6,"area":null},{"id":"2301.04020","title":"Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligence","created":"2022-12-13","cited_by_count":6,"area":null},{"id":"2309.14770","title":"KERMIT: Knowledge Graph Completion of Enhanced Relation Modeling with Inverse Transformation","created":"2023-09-26","cited_by_count":6,"area":null},{"id":"2110.08810","title":"Learning First-Order Rules with Relational Path Contrast for Inductive Relation Reasoning","created":"2021-10-17","cited_by_count":5,"area":null},{"id":"2205.12898","title":"Reasoning over Logically Interacted Conditions for Question Answering","created":"2022-05-25","cited_by_count":3,"area":null},{"id":"2205.15762","title":"Knowledge Enhanced Neural Networks for relational domains","created":"2022-05-31","cited_by_count":3,"area":null},{"id":"2408.05773","title":"Neurosymbolic Methods for Rule Mining","created":"2024-08-11","cited_by_count":1,"area":null},{"id":"2102.07007","title":"A Statistical Relational Approach to Learning Distance-based GCNs","created":"2021-02-13","cited_by_count":0,"area":null},{"id":"2112.06189","title":"An original model for multi-target learning of logical rules for knowledge graph reasoning","created":"2021-12-12","cited_by_count":0,"area":null},{"id":"2112.09933","title":"DegreEmbed: incorporating entity embedding into logic rule learning for knowledge graph reasoning","created":"2021-12-18","cited_by_count":0,"area":null},{"id":"2211.04693","title":"Deep Explainable Learning with Graph Based Data Assessing and Rule Reasoning","created":"2022-11-09","cited_by_count":0,"area":null},{"id":"2308.06094","title":"Reinforcement Logic Rule Learning for Temporal Point Processes","created":"2023-08-11","cited_by_count":0,"area":null},{"id":"2309.11528","title":"Learning Complete Topology-Aware Correlations Between Relations for Inductive Link Prediction","created":"2023-09-20","cited_by_count":0,"area":null},{"id":"2411.11149","title":"From Primes to Paths: Enabling Fast Multi-Relational Graph Analysis","created":"2024-11-17","cited_by_count":0,"area":null}],"next_cursor":null}