{"total":15,"rows":[{"id":"2210.05801","title":"Linkless Link Prediction via Relational Distillation","created":"2022-10-11","cited_by_count":39,"area":null},{"id":"2207.07888","title":"SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks","created":"2022-07-16","cited_by_count":37,"area":null},{"id":"2305.10758","title":"Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effective GNN-to-MLP Distillation Framework","created":"2023-05-18","cited_by_count":24,"area":null},{"id":"2304.14593","title":"Deep Graph Reprogramming","created":"2023-04-28","cited_by_count":22,"area":null},{"id":"2303.10139","title":"Distill n' Explain: explaining graph neural networks using simple surrogates","created":"2023-03-17","cited_by_count":18,"area":null},{"id":"2310.06369","title":"Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks","created":"2023-10-10","cited_by_count":6,"area":null},{"id":"2409.06748","title":"EasyST: A Simple Framework for Spatio-Temporal Prediction","created":"2024-09-10","cited_by_count":6,"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":"2411.03223","title":"Beyond Grid Data: Exploring Graph Neural Networks for Earth Observation","created":"2024-11-05","cited_by_count":3,"area":null},{"id":"2604.03154","title":"DSBD: Dual-Aligned Structural Basis Distillation for Graph Domain Adaptation","created":"2026-04-03","cited_by_count":2,"area":null},{"id":"2304.06038","title":"Knowledge-Distilled Graph Neural Networks for Personalized Epileptic Seizure Detection","created":"2023-04-03","cited_by_count":1,"area":null},{"id":"2405.04114","title":"Acceleration Algorithms in GNNs: A Survey","created":"2024-05-07","cited_by_count":0,"area":null},{"id":"2506.13015","title":"Geometric Embedding Alignment via Curvature Matching in Transfer Learning","created":"2025-06-16","cited_by_count":0,"area":null},{"id":"2604.10882","title":"DIB-OD: Preserving the Invariant Core for Robust Heterogeneous Graph Adaptation via Decoupled Information Bottleneck and Online Distillation","created":"2026-04-13","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}],"next_cursor":null}