{"total":38,"rows":[{"id":"2306.10759","title":"SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations","created":"2023-06-19","cited_by_count":133,"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":"2205.13892","title":"EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks","created":"2022-05-27","cited_by_count":26,"area":null},{"id":"2310.10121","title":"From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and Beyond","created":"2023-10-16","cited_by_count":26,"area":null},{"id":"2210.15956","title":"Generalized Laplacian Positional Encoding for Graph Representation Learning","created":"2022-10-28","cited_by_count":21,"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":"2203.16939","title":"Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs","created":"2022-03-31","cited_by_count":16,"area":null},{"id":"2307.09768","title":"How Curvature Enhance the Adaptation Power of Framelet GCNs","created":"2023-07-19","cited_by_count":13,"area":null},{"id":"2309.02769","title":"Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond","created":"2023-09-06","cited_by_count":13,"area":null},{"id":"2306.07948","title":"Optimal Inference in Contextual Stochastic Block Models","created":"2023-06-06","cited_by_count":12,"area":null},{"id":"2410.03276","title":"Sm: enhanced localization in Multiple Instance Learning for medical imaging classification","created":"2024-10-04","cited_by_count":10,"area":null},{"id":"2201.12994","title":"MGNN: Graph Neural Networks Inspired by Distance Geometry Problem","created":"2022-01-31","cited_by_count":8,"area":null},{"id":"2402.15326","title":"Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory","created":"2024-02-23","cited_by_count":8,"area":null},{"id":"2211.06218","title":"Total Variation Graph Neural Networks","created":"2022-11-11","cited_by_count":7,"area":null},{"id":"2401.14580","title":"Design Your Own Universe: A Physics-Informed Agnostic Method for Enhancing Graph Neural Networks","created":"2024-01-26","cited_by_count":6,"area":null},{"id":"2403.03666","title":"Provable Filter for Real-world Graph Clustering","created":"2024-03-06","cited_by_count":5,"area":null},{"id":"2409.05100","title":"MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks","created":"2024-09-08","cited_by_count":5,"area":null},{"id":"2406.12841","title":"Demystifying Higher-Order Graph Neural Networks","created":"2024-06-18","cited_by_count":4,"area":null},{"id":"2211.14732","title":"Deep representation learning: Fundamentals, Perspectives, Applications, and Open Challenges","created":"2022-11-27","cited_by_count":3,"area":null},{"id":"2402.03818","title":"Asymptotic generalization error of a single-layer graph convolutional network","created":"2024-02-06","cited_by_count":3,"area":null},{"id":"2206.04471","title":"Towards Understanding Graph Neural Networks: An Algorithm Unrolling Perspective","created":"2022-06-09","cited_by_count":2,"area":null},{"id":"2210.01002","title":"ASGNN: Graph Neural Networks with Adaptive Structure","created":"2022-10-03","cited_by_count":2,"area":null},{"id":"2305.16257","title":"Fast Online Node Labeling for Very Large Graphs","created":"2023-05-25","cited_by_count":2,"area":null},{"id":"2405.16185","title":"Differentiable Cluster Graph Neural Network","created":"2024-05-25","cited_by_count":2,"area":null},{"id":"2501.19089","title":"Resolving Oversmoothing with Opinion Dissensus","created":"2025-01-31","cited_by_count":2,"area":null},{"id":"2503.01361","title":"Statistical physics analysis of graph neural networks: Approaching optimality in the contextual stochastic block model","created":"2025-03-03","cited_by_count":2,"area":null},{"id":"2208.07457","title":"Hypergraphs with Edge-Dependent Vertex Weights: p-Laplacians and Spectral Clustering","created":"2022-08-15","cited_by_count":1,"area":null},{"id":"2305.15639","title":"Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and Training with Non-Linear Diffusion","created":"2023-05-25","cited_by_count":1,"area":null},{"id":"2409.09007","title":"SGFormer: Single-Layer Graph Transformers with Approximation-Free Linear Complexity","created":"2024-09-13","cited_by_count":1,"area":null},{"id":"2210.15092","title":"Generalized Laplacian Regularized Framelet Graph Neural Networks","created":"2022-10-27","cited_by_count":0,"area":null},{"id":"2301.08496","title":"Introducing Expertise Logic into Graph Representation Learning from A Causal Perspective","created":"2023-01-20","cited_by_count":0,"area":null},{"id":"2311.03235","title":"p-Laplacian Transformer","created":"2023-11-06","cited_by_count":0,"area":null},{"id":"2409.19096","title":"Enhancing Robustness of Graph Neural Networks through p-Laplacian","created":"2024-09-27","cited_by_count":0,"area":null},{"id":"2511.06143","title":"Enhancing Robustness of Graph Neural Networks through p-Laplacian","created":"2025-11-08","cited_by_count":0,"area":null},{"id":"2602.17071","title":"AdvSynGNN: Structure-Adaptive Graph Neural Nets via Adversarial Synthesis and Self-Corrective Propagation","created":"2026-02-19","cited_by_count":0,"area":null},{"id":"2603.26136","title":"PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing","created":"2026-03-27","cited_by_count":0,"area":null},{"id":"2608.29496","title":"Target-Aware State-Adaptive $p$-Dirichlet Graph Neural Regression for Non-Invasive Body-Composition Estimation","created":"2026-08-30","cited_by_count":0,"area":null},{"id":"2610.00083","title":"\"very likely\" Means \"uncertain\"? How LLMs Diverge from Humans in Linguistic Uncertainty Quantification","created":"2026-09-06","cited_by_count":0,"area":null}],"next_cursor":null}