{"total":214,"rows":[{"id":"2306.08385","title":"NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification","created":"2023-06-14","cited_by_count":210,"area":null},{"id":"2202.02466","title":"Handling Distribution Shifts on Graphs: An Invariance Perspective","created":"2022-02-05","cited_by_count":164,"area":null},{"id":"2110.07580","title":"Graph Condensation for Graph Neural Networks","created":"2021-10-14","cited_by_count":150,"area":null},{"id":"2202.08235","title":"Data Augmentation for Deep Graph Learning: A Survey","created":"2022-02-16","cited_by_count":133,"area":null},{"id":"2204.08570","title":"A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability","created":"2022-04-18","cited_by_count":118,"area":null},{"id":"2201.06367","title":"Towards Unsupervised Deep Graph Structure Learning","created":"2022-01-17","cited_by_count":114,"area":null},{"id":"2107.02392","title":"Dirichlet Energy Constrained Learning for Deep Graph Neural Networks","created":"2021-07-06","cited_by_count":97,"area":null},{"id":"2301.09474","title":"DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion","created":"2023-01-23","cited_by_count":87,"area":null},{"id":"2112.08903","title":"Graph Structure Learning with Variational Information Bottleneck","created":"2021-12-16","cited_by_count":81,"area":null},{"id":"2104.09036","title":"Mining Latent Structures for Multimedia Recommendation","created":"2021-04-19","cited_by_count":79,"area":null},{"id":"2110.11842","title":"Multi-view Contrastive Graph Clustering","created":"2021-10-22","cited_by_count":76,"area":null},{"id":"2304.05055","title":"A Comprehensive Survey on Deep Graph Representation Learning","created":"2023-04-11","cited_by_count":72,"area":null},{"id":"2103.03036","title":"A Survey on Graph Structure Learning: Progress and Opportunities","created":"2021-03-04","cited_by_count":71,"area":null},{"id":"2210.03561","title":"Empowering Graph Representation Learning with Test-Time Graph Transformation","created":"2022-10-07","cited_by_count":67,"area":null},{"id":"2212.02374","title":"On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks","created":"2022-12-05","cited_by_count":64,"area":null},{"id":"2202.08871","title":"Graph Data Augmentation for Graph Machine Learning: A Survey","created":"2022-02-17","cited_by_count":62,"area":null},{"id":"2403.04468","title":"A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges","created":"2024-03-07","cited_by_count":54,"area":null},{"id":"2112.08331","title":"Model Stealing Attacks Against Inductive Graph Neural Networks","created":"2021-12-15","cited_by_count":50,"area":null},{"id":"2310.05174","title":"GSLB: The Graph Structure Learning Benchmark","created":"2023-10-08","cited_by_count":50,"area":null},{"id":"2310.09192","title":"Does Graph Distillation See Like Vision Dataset Counterpart?","created":"2023-10-13","cited_by_count":45,"area":null},{"id":"2407.01290","title":"Hypformer: Exploring Efficient Transformer Fully in Hyperbolic Space","created":"2024-07-01","cited_by_count":43,"area":null},{"id":"2107.07994","title":"Property-Aware Relation Networks for Few-Shot Molecular Property Prediction","created":"2021-07-16","cited_by_count":41,"area":null},{"id":"2405.09591","title":"A Comprehensive Survey on Data Augmentation","created":"2024-05-15","cited_by_count":40,"area":null},{"id":"2104.07886","title":"Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks","created":"2021-04-16","cited_by_count":38,"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":"2203.05880","title":"Multi-modal Graph Learning for Disease Prediction","created":"2022-03-11","cited_by_count":34,"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":"2402.15183","title":"GraphEdit: Large Language Models for Graph Structure Learning","created":"2024-02-23","cited_by_count":33,"area":null},{"id":"2212.12738","title":"T2-GNN: Graph Neural Networks for Graphs with Incomplete Features and Structure via Teacher-Student Distillation","created":"2022-12-24","cited_by_count":32,"area":"distill"},{"id":"2208.08302","title":"Position-aware Structure Learning for Graph Topology-imbalance by Relieving Under-reaching and Over-squashing","created":"2022-08-17","cited_by_count":31,"area":null},{"id":"2201.06885","title":"Evidence-aware Fake News Detection with Graph Neural Networks","created":"2022-01-18","cited_by_count":30,"area":null},{"id":"2306.10280","title":"OpenGSL: A Comprehensive Benchmark for Graph Structure Learning","created":"2023-06-17","cited_by_count":30,"area":null},{"id":"2211.11176","title":"Modeling Multivariate Biosignals With Graph Neural Networks and Structured State Space Models","created":"2022-11-21","cited_by_count":29,"area":"ssm"},{"id":"2310.02156","title":"Probabilistically Rewired Message-Passing Neural Networks","created":"2023-10-03","cited_by_count":26,"area":null},{"id":"2305.18457","title":"Learning Strong Graph Neural Networks with Weak Information","created":"2023-05-29","cited_by_count":25,"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":"2209.08264","title":"Make Heterophily Graphs Better Fit GNN: A Graph Rewiring Approach","created":"2022-09-17","cited_by_count":23,"area":null},{"id":"2210.13148","title":"Transformers over Directed Acyclic Graphs","created":"2022-10-24","cited_by_count":23,"area":null},{"id":"2211.16199","title":"Latent Graph Inference using Product Manifolds","created":"2022-11-26","cited_by_count":23,"area":null},{"id":"2107.03813","title":"Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation","created":"2021-07-08","cited_by_count":22,"area":null},{"id":"2208.03903","title":"Semantic Enhanced Text-to-SQL Parsing via Iteratively Learning Schema Linking Graph","created":"2022-08-08","cited_by_count":22,"area":null},{"id":"2305.02759","title":"Disentangled Contrastive Collaborative Filtering","created":"2023-05-04","cited_by_count":22,"area":null},{"id":"2310.04987","title":"Data-centric Graph Learning: A Survey","created":"2023-10-08","cited_by_count":22,"area":null},{"id":"2106.07451","title":"Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions","created":"2021-06-14","cited_by_count":21,"area":null},{"id":"2201.05540","title":"Compact Graph Structure Learning via Mutual Information Compression","created":"2022-01-14","cited_by_count":20,"area":null},{"id":"2205.10014","title":"A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection","created":"2022-05-20","cited_by_count":20,"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":"2303.02186","title":"Causal Deep Learning","created":"2023-03-03","cited_by_count":20,"area":null},{"id":"2305.16174","title":"From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module","created":"2023-05-25","cited_by_count":19,"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":"2207.08629","title":"Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks","created":"2022-07-18","cited_by_count":18,"area":null},{"id":"2302.06299","title":"Homophily-oriented Heterogeneous Graph Rewiring","created":"2023-02-13","cited_by_count":18,"area":null},{"id":"2410.06530","title":"TopoTune : A Framework for Generalized Combinatorial Complex Neural Networks","created":"2024-10-09","cited_by_count":18,"area":null},{"id":"2110.12035","title":"Distance-wise Prototypical Graph Neural Network in Node Imbalance Classification","created":"2021-10-22","cited_by_count":16,"area":null},{"id":"2401.12780","title":"DeepRicci: Self-supervised Graph Structure-Feature Co-Refinement for Alleviating Over-squashing","created":"2024-01-23","cited_by_count":16,"area":null},{"id":"2203.11200","title":"Exploiting Neighbor Effect: Conv-Agnostic GNNs Framework for Graphs with Heterophily","created":"2022-03-19","cited_by_count":15,"area":null},{"id":"2304.11534","title":"Graph Neural Networks for Text Classification: A Survey","created":"2023-04-23","cited_by_count":15,"area":null},{"id":"2309.10979","title":"Towards Data-centric Graph Machine Learning: Review and Outlook","created":"2023-09-20","cited_by_count":15,"area":null},{"id":"2405.17311","title":"Probabilistic Graph Rewiring via Virtual Nodes","created":"2024-05-27","cited_by_count":15,"area":null},{"id":"2212.01515","title":"Orders Are Unwanted: Dynamic Deep Graph Convolutional Network for Personality Detection","created":"2022-12-03","cited_by_count":14,"area":null},{"id":"2302.02609","title":"Improving Domain Generalization with Domain Relations","created":"2023-02-06","cited_by_count":14,"area":null},{"id":"2402.13711","title":"DSLR: Diversity Enhancement and Structure Learning for Rehearsal-based Graph Continual Learning","created":"2024-02-21","cited_by_count":14,"area":null},{"id":"2111.00180","title":"Hierarchical Heterogeneous Graph Representation Learning for Short Text Classification","created":"2021-10-30","cited_by_count":13,"area":null},{"id":"2307.02514","title":"Exploring Multimodal Approaches for Alzheimer's Disease Detection Using Patient Speech Transcript and Audio Data","created":"2023-07-05","cited_by_count":13,"area":null},{"id":"2312.08616","title":"A Generalized Neural Diffusion Framework on Graphs","created":"2023-12-14","cited_by_count":13,"area":null},{"id":"2312.16855","title":"Molecular Property Prediction Based on Graph Structure Learning","created":"2023-12-28","cited_by_count":13,"area":null},{"id":"2401.02143","title":"Graph Neural Networks for Tabular Data Learning: A Survey with Taxonomy and Directions","created":"2024-01-04","cited_by_count":13,"area":null},{"id":"2102.07186","title":"Relation-aware Graph Attention Model With Adaptive Self-adversarial Training","created":"2021-02-14","cited_by_count":12,"area":null},{"id":"2306.11264","title":"GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks","created":"2023-06-20","cited_by_count":12,"area":null},{"id":"2408.07191","title":"Joint Graph Rewiring and Feature Denoising via Spectral Resonance","created":"2024-08-13","cited_by_count":12,"area":null},{"id":"2409.17386","title":"Beyond Redundancy: Information-aware Unsupervised Multiplex Graph Structure Learning","created":"2024-09-25","cited_by_count":12,"area":null},{"id":"2103.04683","title":"Learning Graph Neural Networks with Positive and Unlabeled Nodes","created":"2021-03-08","cited_by_count":11,"area":null},{"id":"2403.03659","title":"Robust Graph Structure Learning under Heterophily","created":"2024-03-06","cited_by_count":11,"area":null},{"id":"2407.19944","title":"Noise-Resilient Unsupervised Graph Representation Learning via Multi-Hop Feature Quality Estimation","created":"2024-07-29","cited_by_count":11,"area":null},{"id":"2411.17350","title":"Correlation-Aware Graph Convolutional Networks for Multi-Label Node Classification","created":"2024-11-26","cited_by_count":11,"area":null},{"id":"2202.07114","title":"Recent Advances in Reliable Deep Graph Learning: Inherent Noise, Distribution Shift, and Adversarial Attack","created":"2022-02-15","cited_by_count":10,"area":null},{"id":"2308.00574","title":"PVG: Progressive Vision Graph for Vision Recognition","created":"2023-08-01","cited_by_count":10,"area":null},{"id":"2310.18735","title":"Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First","created":"2023-10-28","cited_by_count":10,"area":null},{"id":"2206.09345","title":"Finding Diverse and Predictable Subgraphs for Graph Domain Generalization","created":"2022-06-19","cited_by_count":9,"area":null},{"id":"2210.08906","title":"A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities","created":"2022-10-17","cited_by_count":9,"area":null},{"id":"2301.12762","title":"Causality-based CTR Prediction using Graph Neural Networks","created":"2023-01-30","cited_by_count":9,"area":null},{"id":"2302.11396","title":"KGTrust: Evaluating Trustworthiness of SIoT via Knowledge Enhanced Graph Neural Networks","created":"2023-02-22","cited_by_count":9,"area":null},{"id":"2303.11754","title":"Projections of Model Spaces for Latent Graph Inference","created":"2023-03-21","cited_by_count":9,"area":null},{"id":"2308.05309","title":"Homophily-enhanced Structure Learning for Graph Clustering","created":"2023-08-10","cited_by_count":9,"area":null},{"id":"2308.10737","title":"UGSL: A Unified Framework for Benchmarking Graph Structure Learning","created":"2023-08-21","cited_by_count":9,"area":null},{"id":"2310.04314","title":"Latent Graph Inference with Limited Supervision","created":"2023-10-06","cited_by_count":9,"area":null},{"id":"2410.07191","title":"Curb Your Attention: Causal Attention Gating for Robust Trajectory Prediction in Autonomous Driving","created":"2024-09-23","cited_by_count":9,"area":null},{"id":"2301.00015","title":"Self-organization Preserved Graph Structure Learning with Principle of Relevant Information","created":"2022-12-30","cited_by_count":8,"area":null},{"id":"2302.07960","title":"Learning to Substitute Ingredients in Recipes","created":"2023-02-15","cited_by_count":8,"area":null},{"id":"2312.07861","title":"GraphGuard: Detecting and Counteracting Training Data Misuse in Graph Neural Networks","created":"2023-12-13","cited_by_count":8,"area":null},{"id":"2403.09209","title":"LAN: Learning Adaptive Neighbors for Real-Time Insider Threat Detection","created":"2024-03-14","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":"2208.12547","title":"Deep Hypergraph Structure Learning","created":"2022-08-26","cited_by_count":7,"area":null},{"id":"2210.05498","title":"Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural Networks","created":"2022-10-11","cited_by_count":7,"area":null},{"id":"2402.16012","title":"Deep Contrastive Graph Learning with Clustering-Oriented Guidance","created":"2024-02-25","cited_by_count":7,"area":null},{"id":"2407.04949","title":"Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients","created":"2024-07-06","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":"2202.00423","title":"Memory-based Message Passing: Decoupling the Message for Propogation from Discrimination","created":"2022-02-01","cited_by_count":6,"area":null},{"id":"2202.04936","title":"Robust Graph Representation Learning for Local Corruption Recovery","created":"2022-02-10","cited_by_count":6,"area":null},{"id":"2205.00256","title":"Heterogeneous Graph Neural Networks using Self-supervised Reciprocally Contrastive Learning","created":"2022-04-30","cited_by_count":6,"area":null}],"next_cursor":"100"}