{"total":20,"rows":[{"id":"2502.05424","title":"SAMGPT: Text-free Graph Foundation Model for Multi-domain Pre-training and Cross-domain Adaptation","created":"2025-02-08","cited_by_count":62,"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":"2501.15638","title":"A Comprehensive Survey on Self-Interpretable Neural Networks","created":"2025-01-26","cited_by_count":18,"area":null},{"id":"2407.00615","title":"GC-Bench: An Open and Unified Benchmark for Graph Condensation","created":"2024-06-30","cited_by_count":12,"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":"2403.13850","title":"Spatio-Temporal Fluid Dynamics Modeling via Physical-Awareness and Parameter Diffusion Guidance","created":"2024-03-18","cited_by_count":5,"area":null},{"id":"2407.11025","title":"Backdoor Graph Condensation","created":"2024-07-03","cited_by_count":5,"area":null},{"id":"2412.17355","title":"Bi-Directional Multi-Scale Graph Dataset Condensation via Information Bottleneck","created":"2024-12-23","cited_by_count":4,"area":null},{"id":"2505.20807","title":"Simple yet Effective Graph Distillation via Clustering","created":"2025-05-27","cited_by_count":4,"area":null},{"id":"2506.19224","title":"GBGC: Efficient and Adaptive Graph Coarsening via Granular-ball Computing","created":"2025-06-24","cited_by_count":2,"area":null},{"id":"2511.20222","title":"Decoupling and Damping: Structurally-Regularized Gradient Matching for Multimodal Graph Condensation","created":"2025-11-25","cited_by_count":2,"area":null},{"id":"2410.17579","title":"Bonsai: Gradient-free Graph Condensation for Node Classification","created":"2024-10-23","cited_by_count":1,"area":null},{"id":"2601.11135","title":"Context-aware Graph Causality Inference for Few-Shot Molecular Property Prediction","created":"2026-01-16","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":"2405.07892","title":"All Nodes are created Not Equal: Node-Specific Layer Aggregation and Filtration for GNN","created":"2024-05-13","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":"2601.22943","title":"Scalable Topology-Preserving Graph Coarsening: Concepts and Algorithms","created":"2026-01-30","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":"2605.10001","title":"Anchor-guided Hypergraph Condensation with Dual-level Discrimination","created":"2026-05-11","cited_by_count":0,"area":null},{"id":"2606.03839","title":"Text-attributed Graph Condensation via Text Selection and Attribute Matching","created":"2026-06-02","cited_by_count":0,"area":null}],"next_cursor":null}