{"total":118,"rows":[{"id":"2101.00797","title":"Beyond Low-frequency Information in Graph Convolutional Networks","created":"2021-01-04","cited_by_count":362,"area":null},{"id":"2201.07858","title":"Decoupling the Depth and Scope of Graph Neural Networks","created":"2022-01-19","cited_by_count":94,"area":null},{"id":"2109.14285","title":"Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration","created":"2021-09-29","cited_by_count":92,"area":null},{"id":"2110.15777","title":"GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily","created":"2021-10-29","cited_by_count":84,"area":null},{"id":"2104.09036","title":"Mining Latent Structures for Multimedia Recommendation","created":"2021-04-19","cited_by_count":79,"area":null},{"id":"2102.06986","title":"How Framelets Enhance Graph Neural Networks","created":"2021-02-13","cited_by_count":46,"area":null},{"id":"2108.13049","title":"Single Node Injection Attack against Graph Neural Networks","created":"2021-08-30","cited_by_count":45,"area":null},{"id":"2108.05499","title":"Attention-driven Graph Clustering Network","created":"2021-08-12","cited_by_count":40,"area":null},{"id":"2107.04768","title":"DualVGR: A Dual-Visual Graph Reasoning Unit for Video Question Answering","created":"2021-07-10","cited_by_count":35,"area":null},{"id":"2204.11582","title":"Graph-DETR3D: Rethinking Overlapping Regions for Multi-View 3D Object Detection","created":"2022-04-25","cited_by_count":35,"area":null},{"id":"2303.09778","title":"SE-GSL: A General and Effective Graph Structure Learning Framework through Structural Entropy Optimization","created":"2023-03-17","cited_by_count":35,"area":null},{"id":"2207.00012","title":"Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN","created":"2022-06-30","cited_by_count":34,"area":null},{"id":"2205.02767","title":"Spiking Graph Convolutional Networks","created":"2022-05-05","cited_by_count":27,"area":null},{"id":"2208.06129","title":"Multiplex Heterogeneous Graph Convolutional Network","created":"2022-08-12","cited_by_count":27,"area":null},{"id":"2308.08235","title":"The Expressive Power of Graph Neural Networks: A Survey","created":"2023-08-16","cited_by_count":27,"area":null},{"id":"2310.04987","title":"Data-centric Graph Learning: A Survey","created":"2023-10-08","cited_by_count":22,"area":null},{"id":"2211.06545","title":"Self-Supervised Graph Structure Refinement for Graph Neural Networks","created":"2022-11-12","cited_by_count":20,"area":null},{"id":"2502.06808","title":"On the Benefits of Attribute-Driven Graph Domain Adaptation","created":"2025-02-04","cited_by_count":19,"area":null},{"id":"2108.03388","title":"Jointly Attacking Graph Neural Network and its Explanations","created":"2021-08-07","cited_by_count":18,"area":null},{"id":"2111.00678","title":"Latent Structure Mining with Contrastive Modality Fusion for Multimedia Recommendation","created":"2021-11-01","cited_by_count":18,"area":null},{"id":"2209.00793","title":"Structure-Preserving Graph Representation Learning","created":"2022-09-02","cited_by_count":17,"area":null},{"id":"2108.04822","title":"Self-supervised Consensus Representation Learning for Attributed Graph","created":"2021-08-10","cited_by_count":15,"area":null},{"id":"2112.13562","title":"Powerful Graph Convolutioal Networks with Adaptive Propagation Mechanism for Homophily and Heterophily","created":"2021-12-27","cited_by_count":14,"area":null},{"id":"2202.11360","title":"Deep Graph Learning for Anomalous Citation Detection","created":"2022-02-23","cited_by_count":14,"area":null},{"id":"2203.10280","title":"Meta-Weight Graph Neural Network: Push the Limits Beyond Global Homophily","created":"2022-03-19","cited_by_count":14,"area":null},{"id":"2105.11866","title":"GraphFM: Graph Factorization Machines for Feature Interaction Modeling","created":"2021-05-25","cited_by_count":13,"area":null},{"id":"2211.09155","title":"Learnable Graph Convolutional Network and Feature Fusion for Multi-view Learning","created":"2022-11-16","cited_by_count":13,"area":null},{"id":"2210.12384","title":"The Devil is in the Conflict: Disentangled Information Graph Neural Networks for Fraud Detection","created":"2022-10-22","cited_by_count":11,"area":null},{"id":"2111.05548","title":"Deep Attention-guided Graph Clustering with Dual Self-supervision","created":"2021-11-10","cited_by_count":10,"area":null},{"id":"2205.12784","title":"TrustGNN: Graph Neural Network based Trust Evaluation via Learnable Propagative and Composable Nature","created":"2022-05-25","cited_by_count":10,"area":null},{"id":"2110.03865","title":"Stable Prediction on Graphs with Agnostic Distribution Shift","created":"2021-10-08","cited_by_count":9,"area":null},{"id":"2203.09020","title":"Graph Augmentation Learning","created":"2022-03-17","cited_by_count":9,"area":null},{"id":"2403.16137","title":"A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective","created":"2024-03-24","cited_by_count":9,"area":null},{"id":"2406.19258","title":"Leveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers","created":"2024-06-27","cited_by_count":9,"area":null},{"id":"2101.06855","title":"GraphAttacker: A General Multi-Task GraphAttack Framework","created":"2021-01-18","cited_by_count":8,"area":null},{"id":"2307.11981","title":"Collaborative Graph Neural Networks for Attributed Network Embedding","created":"2023-07-22","cited_by_count":8,"area":null},{"id":"2402.11837","title":"Self-Guided Robust Graph Structure Refinement","created":"2024-02-19","cited_by_count":8,"area":null},{"id":"2106.08848","title":"Data Augmentation for Graph Convolutional Network on Semi-Supervised Classification","created":"2021-06-16","cited_by_count":7,"area":null},{"id":"2108.13650","title":"Heterogeneous Graph Neural Network with Multi-view Representation Learning","created":"2021-08-31","cited_by_count":7,"area":null},{"id":"2311.05185","title":"Mixture of Weak & Strong Experts on Graphs","created":"2023-11-09","cited_by_count":7,"area":null},{"id":"2104.03583","title":"Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed","created":"2021-04-08","cited_by_count":6,"area":null},{"id":"2204.09508","title":"BSAL: A Framework of Bi-component Structure and Attribute Learning for Link Prediction","created":"2022-04-18","cited_by_count":6,"area":null},{"id":"2207.13235","title":"Mid-level Representation Enhancement and Graph Embedded Uncertainty Suppressing for Facial Expression Recognition","created":"2022-07-27","cited_by_count":6,"area":null},{"id":"2306.13854","title":"Similarity Preserving Adversarial Graph Contrastive Learning","created":"2023-06-24","cited_by_count":6,"area":null},{"id":"2308.06801","title":"SAILOR: Structural Augmentation Based Tail Node Representation Learning","created":"2023-08-13","cited_by_count":6,"area":null},{"id":"2406.09675","title":"A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness","created":"2024-06-14","cited_by_count":6,"area":null},{"id":"2303.06344","title":"Graph Contrastive Learning under Heterophily via Graph Filters","created":"2023-03-11","cited_by_count":5,"area":null},{"id":"2310.11025","title":"SignGT: Signed Attention-based Graph Transformer for Graph Representation Learning","created":"2023-10-17","cited_by_count":5,"area":null},{"id":"2406.19249","title":"NTFormer: A Composite Node Tokenized Graph Transformer for Node Classification","created":"2024-06-27","cited_by_count":5,"area":null},{"id":"2502.08101","title":"Rethinking Tokenized Graph Transformers for Node Classification","created":"2025-02-12","cited_by_count":5,"area":null},{"id":"2108.08456","title":"Blockchain Phishing Scam Detection via Multi-channel Graph Classification","created":"2021-08-19","cited_by_count":4,"area":null},{"id":"2301.10956","title":"Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure","created":"2023-01-26","cited_by_count":4,"area":null},{"id":"2308.03666","title":"Bridging Trustworthiness and Open-World Learning: An Exploratory Neural Approach for Enhancing Interpretability, Generalization, and Robustness","created":"2023-08-07","cited_by_count":4,"area":null},{"id":"2401.09071","title":"Rethinking Spectral Graph Neural Networks with Spatially Adaptive Filtering","created":"2024-01-17","cited_by_count":4,"area":null},{"id":"2407.17816","title":"NC-NCD: Novel Class Discovery for Node Classification","created":"2024-07-25","cited_by_count":4,"area":null},{"id":"2107.07737","title":"EGC2: Enhanced Graph Classification with Easy Graph Compression","created":"2021-07-16","cited_by_count":3,"area":null},{"id":"2301.04318","title":"Beyond Graph Convolutional Network: An Interpretable Regularizer-centered Optimization Framework","created":"2023-01-11","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":"2401.15584","title":"DGNN: Decoupled Graph Neural Networks with Structural Consistency between Attribute and Graph Embedding Representations","created":"2024-01-28","cited_by_count":3,"area":null},{"id":"2410.08524","title":"IGNN-Solver: A Graph Neural Solver for Implicit Graph Neural Networks","created":"2024-10-11","cited_by_count":3,"area":null},{"id":"2504.06649","title":"GRAIN: Multi-Granular and Implicit Information Aggregation Graph Neural Network for Heterophilous Graphs","created":"2025-04-09","cited_by_count":3,"area":null},{"id":"2505.23345","title":"Graph Positional Autoencoders as Self-supervised Learners","created":"2025-05-29","cited_by_count":3,"area":null},{"id":"2104.05225","title":"Edgeless-GNN: Unsupervised Representation Learning for Edgeless Nodes","created":"2021-04-12","cited_by_count":2,"area":null},{"id":"2105.06715","title":"Maximizing Mutual Information Across Feature and Topology Views for Learning Graph Representations","created":"2021-05-14","cited_by_count":2,"area":null},{"id":"2110.07869","title":"DPGNN: Dual-Perception Graph Neural Network for Representation Learning","created":"2021-10-15","cited_by_count":2,"area":null},{"id":"2304.06336","title":"Attributed Multi-order Graph Convolutional Network for Heterogeneous Graphs","created":"2023-04-13","cited_by_count":2,"area":null},{"id":"2505.20992","title":"Efficient Identity and Position Graph Embedding via Spectral-Based Random Feature Aggregation","created":"2025-05-27","cited_by_count":2,"area":null},{"id":"2102.03302","title":"Self-Supervised Deep Graph Embedding with High-Order Information Fusion for Community Discovery","created":"2021-02-05","cited_by_count":1,"area":null},{"id":"2105.14490","title":"Relational Graph Neural Network Design via Progressive Neural Architecture Search","created":"2021-05-30","cited_by_count":1,"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":"2211.00277","title":"HFN: Heterogeneous Feature Network for Multivariate Time Series Anomaly Detection","created":"2022-11-01","cited_by_count":1,"area":null},{"id":"2212.01749","title":"Semantic Graph Neural Network with Multi-measure Learning for Semi-supervised Classification","created":"2022-12-04","cited_by_count":1,"area":null},{"id":"2212.05124","title":"Multi-view Graph Convolutional Networks with Differentiable Node Selection","created":"2022-12-09","cited_by_count":1,"area":null},{"id":"2305.17898","title":"Convolutional neural network based on sparse graph attention mechanism for MRI super-resolution","created":"2023-05-29","cited_by_count":1,"area":null},{"id":"2311.14902","title":"Parkinson's Disease Classification Using Contrastive Graph Cross-View Learning with Multimodal Fusion of SPECT Images and Clinical Features","created":"2023-11-25","cited_by_count":1,"area":null},{"id":"2407.16726","title":"Topology Reorganized Graph Contrastive Learning with Mitigating Semantic Drift","created":"2024-07-23","cited_by_count":1,"area":null},{"id":"2410.09128","title":"TIGER: Temporally Improved Graph Entity Linker","created":"2024-10-11","cited_by_count":1,"area":null},{"id":"2411.01169","title":"Bi-Level Graph Structure Learning for Next POI Recommendation","created":"2024-11-02","cited_by_count":1,"area":null},{"id":"2411.03744","title":"Graph Neural Networks with Coarse- and Fine-Grained Division for Mitigating Label Sparsity and Noise","created":"2024-11-06","cited_by_count":1,"area":null},{"id":"2411.04356","title":"GaGSL: Global-augmented Graph Structure Learning via Graph Information Bottleneck","created":"2024-11-07","cited_by_count":1,"area":null},{"id":"2504.21206","title":"FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs","created":"2025-04-29","cited_by_count":1,"area":null},{"id":"2604.23324","title":"Layer Embedding Deep Fusion Graph Neural Network","created":"2026-04-25","cited_by_count":1,"area":null},{"id":"2605.08679","title":"Attention-based graph neural networks: a survey","created":"2026-05-09","cited_by_count":1,"area":null},{"id":"2104.13046","title":"A Knowledge Enhanced Learning and Semantic Composition Model for Multi-Claim Fact Checking","created":"2021-04-27","cited_by_count":0,"area":null},{"id":"2106.03723","title":"Self-Supervised Graph Learning with Proximity-based Views and Channel Contrast","created":"2021-06-07","cited_by_count":0,"area":null},{"id":"2106.05455","title":"AKE-GNN: Effective Graph Learning with Adaptive Knowledge Exchange","created":"2021-06-10","cited_by_count":0,"area":null},{"id":"2110.09182","title":"Graph Partner Neural Networks for Semi-Supervised Learning on Graphs","created":"2021-10-18","cited_by_count":0,"area":null},{"id":"2111.10102","title":"Graph Neural Networks with Feature and Structure Aware Random Walk","created":"2021-11-19","cited_by_count":0,"area":null},{"id":"2112.03273","title":"Dynamic Graph Learning-Neural Network for Multivariate Time Series Modeling","created":"2021-12-06","cited_by_count":0,"area":null},{"id":"2204.05258","title":"Multi-view graph structure learning using subspace merging on Grassmann manifold","created":"2022-04-11","cited_by_count":0,"area":null},{"id":"2205.03753","title":"Select and Calibrate the Low-confidence: Dual-Channel Consistency based Graph Convolutional Networks","created":"2022-05-08","cited_by_count":0,"area":null},{"id":"2205.14303","title":"Deep Embedded Clustering with Distribution Consistency Preservation for Attributed Networks","created":"2022-05-28","cited_by_count":0,"area":null},{"id":"2206.10142","title":"Propagation with Adaptive Mask then Training for Node Classification on Attributed Networks","created":"2022-06-21","cited_by_count":0,"area":null},{"id":"2210.05676","title":"Towards Consistency and Complementarity: A Multiview Graph Information Bottleneck Approach","created":"2022-10-11","cited_by_count":0,"area":null},{"id":"2210.05947","title":"Adaptive Dual Channel Convolution Hypergraph Representation Learning for Technological Intellectual Property","created":"2022-10-12","cited_by_count":0,"area":null},{"id":"2211.00565","title":"Revisiting Heterophily in Graph Convolution Networks by Learning Representations Across Topological and Feature Spaces","created":"2022-11-01","cited_by_count":0,"area":null},{"id":"2211.07845","title":"Neighborhood Convolutional Network: A New Paradigm of Graph Neural Networks for Node Classification","created":"2022-11-15","cited_by_count":0,"area":null},{"id":"2304.01242","title":"Enhancing Clinical Evidence Recommendation with Multi-Channel Heterogeneous Learning on Evidence Graphs","created":"2023-04-03","cited_by_count":0,"area":null},{"id":"2311.02116","title":"Resist Label Noise with PGM for Graph Neural Networks","created":"2023-11-03","cited_by_count":0,"area":null},{"id":"2312.09498","title":"Neural Gaussian Similarity Modeling for Differential Graph Structure Learning","created":"2023-12-15","cited_by_count":0,"area":null}],"next_cursor":"100"}