{"total":30,"rows":[{"id":"2206.04355","title":"Graph Attention Multi-Layer Perceptron","created":"2022-06-09","cited_by_count":83,"area":null},{"id":"2104.14210","title":"FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning","created":"2021-04-29","cited_by_count":68,"area":null},{"id":"2110.14377","title":"Node Dependent Local Smoothing for Scalable Graph Learning","created":"2021-10-27","cited_by_count":45,"area":null},{"id":"2212.09034","title":"Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs","created":"2022-12-18","cited_by_count":42,"area":null},{"id":"2203.00638","title":"PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm","created":"2022-03-01","cited_by_count":37,"area":null},{"id":"2206.04361","title":"Model Degradation Hinders Deep Graph Neural Networks","created":"2022-06-09","cited_by_count":26,"area":null},{"id":"2312.16560","title":"Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching","created":"2023-12-27","cited_by_count":24,"area":null},{"id":"2108.00955","title":"Evaluating Deep Graph Neural Networks","created":"2021-08-02","cited_by_count":19,"area":null},{"id":"2107.11789","title":"ROD: Reception-aware Online Distillation for Sparse Graphs","created":"2021-07-25","cited_by_count":18,"area":null},{"id":"2101.02326","title":"GraphHop: An Enhanced Label Propagation Method for Node Classification","created":"2021-01-07","cited_by_count":15,"area":null},{"id":"2109.09426","title":"A Meta-Learning Approach for Training Explainable Graph Neural Networks","created":"2021-09-20","cited_by_count":15,"area":null},{"id":"2107.04755","title":"Beyond Low-pass Filtering: Graph Convolutional Networks with Automatic Filtering","created":"2021-07-10","cited_by_count":14,"area":null},{"id":"2506.13083","title":"Uncertainty-Aware Graph Neural Networks: A Multi-Hop Evidence Fusion Approach","created":"2025-06-16","cited_by_count":14,"area":null},{"id":"2508.10594","title":"FreeGAD: A Training-Free yet Effective Approach for Graph Anomaly Detection","created":"2025-08-14","cited_by_count":10,"area":null},{"id":"2111.15119","title":"Aerial Images Meet Crowdsourced Trajectories: A New Approach to Robust Road Extraction","created":"2021-11-30","cited_by_count":6,"area":null},{"id":"2103.07295","title":"Adversarial Graph Disentanglement","created":"2021-03-12","cited_by_count":5,"area":null},{"id":"2104.09880","title":"GMLP: Building Scalable and Flexible Graph Neural Networks with Feature-Message Passing","created":"2021-04-20","cited_by_count":5,"area":null},{"id":"2108.10097","title":"Graph Attention MLP with Reliable Label Utilization","created":"2021-08-23","cited_by_count":3,"area":null},{"id":"2211.10627","title":"EGRC-Net: Embedding-induced Graph Refinement Clustering Network","created":"2022-11-19","cited_by_count":3,"area":null},{"id":"2303.01265","title":"Steering Graph Neural Networks with Pinning Control","created":"2023-03-02","cited_by_count":3,"area":null},{"id":"2310.05105","title":"How Graph Neural Networks Learn: Lessons from Training Dynamics","created":"2023-10-08","cited_by_count":3,"area":null},{"id":"2509.01170","title":"ADMP-GNN: Adaptive Depth Message Passing GNN","created":"2025-09-01","cited_by_count":3,"area":null},{"id":"2302.11479","title":"Drop Edges and Adapt: a Fairness Enforcing Fine-tuning for Graph Neural Networks","created":"2023-02-22","cited_by_count":2,"area":null},{"id":"2311.12823","title":"EWasteNet: A Two-Stream Data Efficient Image Transformer Approach for E-Waste Classification","created":"2023-09-28","cited_by_count":2,"area":null},{"id":"2403.13268","title":"Unifews: You Need Fewer Operations for Efficient Graph Neural Networks","created":"2024-03-20","cited_by_count":2,"area":null},{"id":"2505.18088","title":"Early-Exit Graph Neural Networks","created":"2025-05-23","cited_by_count":2,"area":null},{"id":"2206.07253","title":"TeKo: Text-Rich Graph Neural Networks with External Knowledge","created":"2022-06-15","cited_by_count":1,"area":null},{"id":"2206.08582","title":"DFG-NAS: Deep and Flexible Graph Neural Architecture Search","created":"2022-06-17","cited_by_count":1,"area":null},{"id":"2401.01233","title":"GEN: A Practical Alternative to Graph Transformers for Long-Range Graph Modeling","created":"2024-01-02","cited_by_count":0,"area":null},{"id":"2606.22167","title":"Early-Exit Graph Neural Networks for Link Prediction","created":"2026-06-20","cited_by_count":0,"area":null}],"next_cursor":null}