{"total":57,"rows":[{"id":"2404.14928","title":"Graph Machine Learning in the Era of Large Language Models (LLMs)","created":"2024-04-23","cited_by_count":33,"area":null},{"id":"2407.09777","title":"Graph Transformers: A Survey","created":"2024-07-13","cited_by_count":32,"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":"2402.05011","title":"Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching","created":"2024-02-07","cited_by_count":28,"area":null},{"id":"2405.13707","title":"Rethinking and Accelerating Graph Condensation: A Training-Free Approach with Class Partition","created":"2024-05-22","cited_by_count":23,"area":null},{"id":"2402.05962","title":"EXGC: Bridging Efficiency and Explainability in Graph Condensation","created":"2024-02-05","cited_by_count":20,"area":null},{"id":"2405.14260","title":"Graph Sparsification via Mixture of Graphs","created":"2024-05-23","cited_by_count":17,"area":"moe"},{"id":"2503.23167","title":"Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks","created":"2025-03-29","cited_by_count":14,"area":null},{"id":"2402.02000","title":"A Survey on Graph Condensation","created":"2024-02-03","cited_by_count":9,"area":null},{"id":"2402.04924","title":"Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching","created":"2024-02-07","cited_by_count":8,"area":null},{"id":"2406.13200","title":"RobGC: Towards Robust Graph Condensation","created":"2024-06-19","cited_by_count":8,"area":null},{"id":"2505.16860","title":"GCAL: Adapting Graph Models to Evolving Domain Shifts","created":"2025-05-22","cited_by_count":8,"area":null},{"id":"2406.16715","title":"GC4NC: A Benchmark Framework for Graph Condensation on Node Classification with New Insights","created":"2024-06-24","cited_by_count":7,"area":null},{"id":"2501.15282","title":"AutoG: Towards automatic graph construction from tabular data","created":"2025-01-25","cited_by_count":7,"area":null},{"id":"2502.10556","title":"Recent Advances in Malware Detection: Graph Learning and Explainability","created":"2025-02-14","cited_by_count":7,"area":null},{"id":"2411.17063","title":"Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning","created":"2024-11-26","cited_by_count":6,"area":null},{"id":"2502.17614","title":"Scalable Graph Condensation with Evolving Capabilities","created":"2025-02-24","cited_by_count":6,"area":null},{"id":"2405.14246","title":"GCondenser: Benchmarking Graph Condensation","created":"2024-05-23","cited_by_count":5,"area":null},{"id":"2407.08064","title":"TinyGraph: Joint Feature and Node Condensation for Graph Neural Networks","created":"2024-07-10","cited_by_count":5,"area":null},{"id":"2407.11025","title":"Backdoor Graph Condensation","created":"2024-07-03","cited_by_count":5,"area":null},{"id":"2505.20807","title":"Simple yet Effective Graph Distillation via Clustering","created":"2025-05-27","cited_by_count":4,"area":null},{"id":"2506.14570","title":"From Points to Places: Towards Human Mobility-Driven Spatiotemporal Foundation Models via Understanding Places","created":"2025-06-17","cited_by_count":3,"area":null},{"id":"2505.21117","title":"ReassembleNet: Learnable Keypoints and Diffusion for 2D Fresco Reconstruction","created":"2025-05-27","cited_by_count":2,"area":null},{"id":"2506.19224","title":"GBGC: Efficient and Adaptive Graph Coarsening via Granular-ball Computing","created":"2025-06-24","cited_by_count":2,"area":null},{"id":"2510.27474","title":"Spectral Neural Graph Sparsification","created":"2025-10-31","cited_by_count":2,"area":null},{"id":"2411.19392","title":"Scale-aware Message Passing For Graph Node Classification","created":"2024-11-28","cited_by_count":1,"area":null},{"id":"2412.08835","title":"Grothendieck Graph Neural Networks Framework: An Algebraic Platform for Crafting Topology-Aware GNNs","created":"2024-12-12","cited_by_count":1,"area":null},{"id":"2412.16250","title":"Training-free Heterogeneous Graph Condensation via Data Selection","created":"2024-12-20","cited_by_count":1,"area":null},{"id":"2506.13099","title":"Dynamic Graph Condensation","created":"2025-06-16","cited_by_count":1,"area":null},{"id":"2507.02921","title":"PlaceRep: Geospatial Place Representation Learning from Large-Scale Point-of-Interest Data","created":"2025-06-25","cited_by_count":1,"area":null},{"id":"2508.14330","title":"Multi-view Graph Condensation via Tensor Decomposition","created":"2025-08-20","cited_by_count":1,"area":null},{"id":"2510.22329","title":"Graph-Coarsening Approach for the Capacitated Vehicle Routing Problem with Time Windows","created":"2025-10-25","cited_by_count":1,"area":null},{"id":"2601.19946","title":"MK-SGC-SC: Multiple Kernel Guided Sparse Graph Construction in Spectral Clustering for Unsupervised Speaker Diarization","created":"2026-01-24","cited_by_count":1,"area":null},{"id":"2605.18893","title":"Position: Graph Condensation Needs a Reset -- Move Beyond Full-dataset Training and Model-Dependence","created":"2026-05-17","cited_by_count":1,"area":null},{"id":"2410.21618","title":"Graph Sparsification for Enhanced Conformal Prediction in Graph Neural Networks","created":"2024-10-28","cited_by_count":0,"area":null},{"id":"2411.08758","title":"ScaleNet: Scale Invariance Learning in Directed Graphs","created":"2024-11-13","cited_by_count":0,"area":null},{"id":"2412.17961","title":"Extending Graph Condensation to Multi-Label Datasets: A Benchmark Study","created":"2024-12-23","cited_by_count":0,"area":null},{"id":"2503.12156","title":"Efficient and Privacy-Preserved Link Prediction via Condensed Graphs","created":"2025-03-15","cited_by_count":0,"area":null},{"id":"2504.13034","title":"Inference-friendly Graph Compression for Graph Neural Networks","created":"2025-04-17","cited_by_count":0,"area":null},{"id":"2505.12323","title":"GraphFLEx: Structure Learning Framework for Large Expanding Graphs","created":"2025-05-18","cited_by_count":0,"area":null},{"id":"2509.14722","title":"Towards Pre-trained Graph Condensation via Optimal Transport","created":"2025-09-18","cited_by_count":0,"area":null},{"id":"2509.25706","title":"Adaptive Graph Coarsening for Efficient GNN Training","created":"2025-09-30","cited_by_count":0,"area":null},{"id":"2510.21906","title":"Structure-Aware Cooperative Ensemble Evolutionary Optimization on Combinatorial Problems with Multimodal Large Language Models","created":"2025-10-24","cited_by_count":0,"area":"mllm"},{"id":"2511.02196","title":"BoolSkeleton: Boolean Network Skeletonization via Homogeneous Pattern Reduction","created":"2025-11-04","cited_by_count":0,"area":null},{"id":"2512.24327","title":"Topological Spatial Graph Coarsening","created":"2025-12-30","cited_by_count":0,"area":null},{"id":"2603.26456","title":"Fair Data Pre-Processing with Imperfect Attribute Space","created":"2026-03-27","cited_by_count":0,"area":null},{"id":"2605.06814","title":"Model-to-Data Distillation for Graph Neural Networks","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2606.12581","title":"Graph Reduction in Multirelational Networks: A Spreading-Oriented Reduction Benchmark","created":"2026-06-10","cited_by_count":0,"area":null},{"id":"2606.30101","title":"SIR: Structured Image Representations for Explainable Robot Learning","created":"2026-06-29","cited_by_count":0,"area":null},{"id":"2607.03097","title":"Heterogeneous Graph Condensation via Role-Aware Clustering","created":"2026-07-03","cited_by_count":0,"area":null},{"id":"2607.09708","title":"GES-TSP: Graph Edge Sparsification for TSP","created":"2026-06-23","cited_by_count":0,"area":null},{"id":"2607.10969","title":"CGS: Configurable Graph Summarization with Bounded Neighborhood Loss and Query Support","created":"2026-07-13","cited_by_count":0,"area":null},{"id":"2607.21885","title":"Remedying Coarsening-Based GNN Training under Heterophily via Adaptive Complementary Enhancement","created":"2026-07-24","cited_by_count":0,"area":null},{"id":"2607.23338","title":"Does Graph Compression Preserve Signal Propagation?","created":"2026-07-25","cited_by_count":0,"area":null},{"id":"2608.07158","title":"Edge Sparsification via Temporal Forman-Ricci Curvature for Dynamic Graph Learning","created":"2026-08-07","cited_by_count":0,"area":null},{"id":"2609.14045","title":"Data-Efficient Agentic Graph Domain Adaptation via Reliability-Aware Prototype Learning","created":"2026-09-12","cited_by_count":0,"area":"agents"},{"id":"2609.31466","title":"Scaffold: Support Graph Theory Based Sparsification for Graph Neural Networks","created":"2026-09-25","cited_by_count":0,"area":null}],"next_cursor":null}