{"total":23,"rows":[{"id":"2303.14483","title":"Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey","created":"2023-03-25","cited_by_count":140,"area":null},{"id":"2302.01018","title":"Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities","created":"2023-02-02","cited_by_count":61,"area":null},{"id":"2208.09957","title":"Heterogeneous Graph Masked Autoencoders","created":"2022-08-21","cited_by_count":47,"area":null},{"id":"2210.02016","title":"Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization","created":"2022-10-05","cited_by_count":35,"area":null},{"id":"2412.16441","title":"Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees","created":"2024-12-21","cited_by_count":32,"area":null},{"id":"2310.00800","title":"GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation","created":"2023-10-01","cited_by_count":31,"area":null},{"id":"2210.02933","title":"Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering","created":"2022-10-06","cited_by_count":22,"area":null},{"id":"2402.06633","title":"MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction","created":"2024-01-19","cited_by_count":18,"area":null},{"id":"2501.18739","title":"Beyond Message Passing: Neural Graph Pattern Machine","created":"2025-01-30","cited_by_count":17,"area":null},{"id":"2304.05729","title":"Dynamic Graph Representation Learning with Neural Networks: A Survey","created":"2023-04-12","cited_by_count":15,"area":null},{"id":"2411.08550","title":"Graph Neural Networks in Supply Chain Analytics and Optimization: Concepts, Perspectives, Dataset and Benchmarks","created":"2024-11-13","cited_by_count":7,"area":null},{"id":"2512.21106","title":"Semantic Refinement with LLMs for Graph Representations","created":"2025-12-24","cited_by_count":6,"area":null},{"id":"2404.08660","title":"How Does Message Passing Improve Collaborative Filtering?","created":"2024-03-27","cited_by_count":5,"area":null},{"id":"2406.13365","title":"PPT-GNN: A Practical Pre-Trained Spatio-Temporal Graph Neural Network for Network Security","created":"2024-06-19","cited_by_count":2,"area":null},{"id":"2411.04936","title":"Fed-LDR: Federated Local Data-infused Graph Creation with Node-centric Model Refinement","created":"2024-11-07","cited_by_count":2,"area":null},{"id":"2506.17312","title":"Heterogeneous Temporal Hypergraph Neural Network","created":"2025-06-18","cited_by_count":2,"area":null},{"id":"2510.18467","title":"Simple and Efficient Heterogeneous Temporal Graph Neural Network","created":"2025-10-21","cited_by_count":2,"area":null},{"id":"2512.11352","title":"CAT: Can Trust be Predicted with Context-Awareness in Dynamic Heterogeneous Networks?","created":"2025-12-12","cited_by_count":2,"area":null},{"id":"2310.00336","title":"DURENDAL: Graph deep learning framework for temporal heterogeneous networks","created":"2023-09-30","cited_by_count":1,"area":null},{"id":"2606.29972","title":"First-Order Temporal Logic Tensor Networks","created":"2026-06-29","cited_by_count":1,"area":null},{"id":"2209.03144","title":"Representing Social Networks as Dynamic Heterogeneous Graphs","created":"2022-09-02","cited_by_count":0,"area":null},{"id":"2607.27303","title":"THGFM: Dual-Branch Temporal Heterogeneous Graph Fusion Model","created":"2026-07-29","cited_by_count":0,"area":null},{"id":"2609.04779","title":"Dynamic Heterogeneous Graph Representation Learning: A Survey","created":"2026-09-04","cited_by_count":0,"area":null}],"next_cursor":null}