{"total":113,"rows":[{"id":"2106.06663","title":"TDGIA:Effective Injection Attacks on Graph Neural Networks","created":"2021-06-12","cited_by_count":67,"area":null},{"id":"2111.04314","title":"Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine Learning","created":"2021-11-08","cited_by_count":44,"area":null},{"id":"2109.09888","title":"Chemical-Reaction-Aware Molecule Representation Learning","created":"2021-09-21","cited_by_count":36,"area":null},{"id":"2209.07754","title":"On the Robustness of Graph Neural Diffusion to Topology Perturbations","created":"2022-09-16","cited_by_count":30,"area":null},{"id":"2108.05507","title":"Distilling Holistic Knowledge with Graph Neural Networks","created":"2021-08-12","cited_by_count":26,"area":"distill"},{"id":"2308.04268","title":"Teacher-Student Architecture for Knowledge Distillation: A Survey","created":"2023-08-08","cited_by_count":26,"area":"distill"},{"id":"2106.15762","title":"Curvature Graph Neural Network","created":"2021-06-30","cited_by_count":24,"area":null},{"id":"2202.01537","title":"Bending Graphs: Hierarchical Shape Matching using Gated Optimal Transport","created":"2022-02-03","cited_by_count":24,"area":null},{"id":"2310.06396","title":"Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach","created":"2023-10-10","cited_by_count":24,"area":null},{"id":"2310.13590","title":"ReLM: Leveraging Language Models for Enhanced Chemical Reaction Prediction","created":"2023-10-20","cited_by_count":24,"area":null},{"id":"2106.01854","title":"Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning","created":"2021-06-03","cited_by_count":21,"area":null},{"id":"2109.02859","title":"Hyper Meta-Path Contrastive Learning for Multi-Behavior Recommendation","created":"2021-09-07","cited_by_count":21,"area":null},{"id":"2305.04208","title":"Segmentation and Vascular Vectorization for Coronary Artery by Geometry-based Cascaded Neural Network","created":"2023-05-07","cited_by_count":21,"area":null},{"id":"2311.03415","title":"PowerFlowNet: Power Flow Approximation Using Message Passing Graph Neural Networks","created":"2023-11-06","cited_by_count":21,"area":null},{"id":"2307.05541","title":"High Fidelity 3D Hand Shape Reconstruction via Scalable Graph Frequency Decomposition","created":"2023-07-08","cited_by_count":18,"area":null},{"id":"2404.17099","title":"Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND","created":"2024-04-26","cited_by_count":17,"area":null},{"id":"2203.03762","title":"Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-supervision","created":"2022-03-07","cited_by_count":16,"area":null},{"id":"2508.06199","title":"Benchmarking Pretrained Molecular Embedding Models For Molecular Representation Learning","created":"2025-08-08","cited_by_count":15,"area":null},{"id":"2208.09779","title":"Robust Node Classification on Graphs: Jointly from Bayesian Label Transition and Topology-based Label Propagation","created":"2022-08-21","cited_by_count":12,"area":null},{"id":"2301.11378","title":"MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods","created":"2023-01-26","cited_by_count":12,"area":null},{"id":"2410.02392","title":"MANTRA: The Manifold Triangulations Assemblage","created":"2024-10-03","cited_by_count":12,"area":null},{"id":"2108.08230","title":"Predicting Basin Stability of Power Grids using Graph Neural Networks","created":"2021-08-18","cited_by_count":11,"area":null},{"id":"2205.09833","title":"Learning Interface Conditions in Domain Decomposition Solvers","created":"2022-05-19","cited_by_count":11,"area":null},{"id":"2303.16004","title":"A Survey on Malware Detection with Graph Representation Learning","created":"2023-03-28","cited_by_count":11,"area":null},{"id":"2304.07515","title":"S3M: Scalable Statistical Shape Modeling through Unsupervised Correspondences","created":"2023-04-15","cited_by_count":11,"area":null},{"id":"2404.19508","title":"Temporal Graph ODEs for Irregularly-Sampled Time Series","created":"2024-04-30","cited_by_count":11,"area":null},{"id":"2307.08636","title":"PolyGNN: Polyhedron-based Graph Neural Network for 3D Building Reconstruction from Point Clouds","created":"2023-07-17","cited_by_count":10,"area":null},{"id":"2310.19263","title":"A Metadata-Driven Approach to Understand Graph Neural Networks","created":"2023-10-30","cited_by_count":10,"area":null},{"id":"2401.04331","title":"Coupling Graph Neural Networks with Fractional Order Continuous Dynamics: A Robustness Study","created":"2024-01-09","cited_by_count":9,"area":null},{"id":"2308.02051","title":"A Graphical Approach to Document Layout Analysis","created":"2023-08-03","cited_by_count":8,"area":null},{"id":"2406.07640","title":"When is an Embedding Model More Promising than Another?","created":"2024-06-11","cited_by_count":7,"area":null},{"id":"2406.09031","title":"A Comprehensive Graph Pooling Benchmark: Effectiveness, Robustness and Generalizability","created":"2024-06-13","cited_by_count":7,"area":null},{"id":"2505.14699","title":"Benchmarking Graph Neural Networks for Document Layout Analysis in Public Affairs","created":"2025-05-12","cited_by_count":7,"area":null},{"id":"2510.22048","title":"PF$\\Delta$: A Benchmark Dataset for Power Flow under Load, Generation, and Topology Variations","created":"2025-10-24","cited_by_count":7,"area":null},{"id":"2109.05671","title":"Shape-Biased Domain Generalization via Shock Graph Embeddings","created":"2021-09-13","cited_by_count":6,"area":null},{"id":"2110.09726","title":"CGNN: Traffic Classification with Graph Neural Network","created":"2021-10-19","cited_by_count":6,"area":null},{"id":"2112.06033","title":"Spatial Graph Convolutional Neural Network via Structured Subdomain Adaptation and Domain Adversarial Learning for Bearing Fault Diagnosis","created":"2021-12-11","cited_by_count":6,"area":null},{"id":"2402.03466","title":"Physics-Encoded Graph Neural Networks for Deformation Prediction under Contact","created":"2024-02-05","cited_by_count":6,"area":null},{"id":"2510.06860","title":"Towards Generalization of Graph Neural Networks for AC Optimal Power Flow","created":"2025-10-08","cited_by_count":6,"area":null},{"id":"2108.05947","title":"Room Classification on Floor Plan Graphs using Graph Neural Networks","created":"2021-08-12","cited_by_count":5,"area":null},{"id":"2206.03247","title":"Towards better Interpretable and Generalizable AD detection using Collective Artificial Intelligence","created":"2022-06-07","cited_by_count":5,"area":null},{"id":"2304.08640","title":"TAP: A Comprehensive Data Repository for Traffic Accident Prediction in Road Networks","created":"2023-04-17","cited_by_count":5,"area":null},{"id":"2310.01015","title":"EX-Graph: A Pioneering Dataset Bridging Ethereum and X","created":"2023-10-02","cited_by_count":5,"area":null},{"id":"2206.06369","title":"Toward Dynamic Stability Assessment of Power Grid Topologies using Graph Neural Networks","created":"2022-06-10","cited_by_count":4,"area":null},{"id":"2305.01912","title":"MolKD: Distilling Cross-Modal Knowledge in Chemical Reactions for Molecular Property Prediction","created":"2023-05-03","cited_by_count":4,"area":null},{"id":"2312.08223","title":"Patch-wise Graph Contrastive Learning for Image Translation","created":"2023-12-13","cited_by_count":4,"area":null},{"id":"2409.01931","title":"On the design space between molecular mechanics and machine learning force fields","created":"2024-09-03","cited_by_count":4,"area":null},{"id":"2601.08134","title":"How Reliable are Confidence Estimators for Large Reasoning Models? A Systematic Benchmark on High-Stakes Domains","created":"2026-01-13","cited_by_count":4,"area":"lr"},{"id":"2211.03021","title":"Characterizing the Efficiency of Graph Neural Network Frameworks with a Magnifying Glass","created":"2022-11-06","cited_by_count":3,"area":null},{"id":"2212.11130","title":"Towards dynamic stability analysis of sustainable power grids using graph neural networks","created":"2022-12-21","cited_by_count":3,"area":null},{"id":"2305.02901","title":"Single Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learning","created":"2023-05-04","cited_by_count":3,"area":null},{"id":"2402.05373","title":"Unleashing the Infinity Power of Geometry: A Novel Geometry-Aware Transformer (GOAT) for Whole Slide Histopathology Image Analysis","created":"2024-02-08","cited_by_count":3,"area":null},{"id":"2408.11351","title":"Vision HgNN: An Electron-Micrograph is Worth Hypergraph of Hypernodes","created":"2024-08-21","cited_by_count":3,"area":null},{"id":"2505.09361","title":"Efficient Mixed Precision Quantization in Graph Neural Networks","created":"2025-05-14","cited_by_count":3,"area":null},{"id":"2101.05866","title":"Comparisons of Graph Neural Networks on Cancer Classification Leveraging a Joint of Phenotypic and Genetic Features","created":"2021-01-14","cited_by_count":2,"area":null},{"id":"2207.11836","title":"Mitigating the Performance Sacrifice in DP-Satisfied Federated Settings through Graph Contrastive Learning","created":"2022-07-24","cited_by_count":2,"area":null},{"id":"2308.15491","title":"Detecting Inactive Cyberwarriors from Online Forums","created":"2023-08-28","cited_by_count":2,"area":null},{"id":"2311.02326","title":"FragXsiteDTI: Revealing Responsible Segments in Drug-Target Interaction with Transformer-Driven Interpretation","created":"2023-11-04","cited_by_count":2,"area":null},{"id":"2402.00564","title":"A Single Graph Convolution Is All You Need: Efficient Grayscale Image Classification","created":"2024-02-01","cited_by_count":2,"area":null},{"id":"2406.08917","title":"Predicting Fault-Ride-Through Probability of Inverter-Dominated Power Grids using Machine Learning","created":"2024-06-13","cited_by_count":2,"area":null},{"id":"2407.12419","title":"Dirac--Bianconi Graph Neural Networks -- Enabling Non-Diffusive Long-Range Graph Predictions","created":"2024-07-17","cited_by_count":2,"area":null},{"id":"2409.08946","title":"DELTA: Dual Consistency Delving with Topological Uncertainty for Active Graph Domain Adaptation","created":"2024-09-13","cited_by_count":2,"area":null},{"id":"2102.09974","title":"Supporting Financial Inclusion with Graph Machine Learning and Super-App Alternative Data","created":"2021-02-19","cited_by_count":1,"area":null},{"id":"2102.12877","title":"TELESTO: A Graph Neural Network Model for Anomaly Classification in Cloud Services","created":"2021-02-25","cited_by_count":1,"area":null},{"id":"2106.15755","title":"Dual GNNs: Graph Neural Network Learning with Limited Supervision","created":"2021-06-29","cited_by_count":1,"area":null},{"id":"2111.12952","title":"AutoHEnsGNN: Winning Solution to AutoGraph Challenge for KDD Cup 2020","created":"2021-11-25","cited_by_count":1,"area":null},{"id":"2209.01080","title":"Event-Driven Tactile Learning with Location Spiking Neurons","created":"2022-07-23","cited_by_count":1,"area":null},{"id":"2211.08227","title":"Perona: Robust Infrastructure Fingerprinting for Resource-Efficient Big Data Analytics","created":"2022-11-15","cited_by_count":1,"area":null},{"id":"2303.17966","title":"HD-GCN:A Hybrid Diffusion Graph Convolutional Network","created":"2023-03-31","cited_by_count":1,"area":null},{"id":"2306.15155","title":"SENSEi: Input-Sensitive Compilation for Accelerating GNNs","created":"2023-06-27","cited_by_count":1,"area":null},{"id":"2403.15077","title":"GTAGCN: Generalized Topology Adaptive Graph Convolutional Networks","created":"2024-03-22","cited_by_count":1,"area":null},{"id":"2408.15305","title":"Parameter-Efficient Quantized Mixture-of-Experts Meets Vision-Language Instruction Tuning for Semiconductor Electron Micrograph Analysis","created":"2024-08-27","cited_by_count":1,"area":"moe"},{"id":"2411.02542","title":"Enhancing Graph Neural Networks in Large-scale Traffic Incident Analysis with Concurrency Hypothesis","created":"2024-11-04","cited_by_count":1,"area":null},{"id":"2411.16972","title":"Clustering Time Series Data with Gaussian Mixture Embeddings in a Graph Autoencoder Framework","created":"2024-11-25","cited_by_count":1,"area":null},{"id":"2412.02839","title":"Geographical Information Alignment Boosts Traffic Analysis via Transpose Cross-attention","created":"2024-12-03","cited_by_count":1,"area":null},{"id":"2503.10058","title":"Deep Learning Approaches for Anti-Money Laundering on Mobile Transactions: Review, Framework, and Directions","created":"2025-03-13","cited_by_count":1,"area":null},{"id":"2507.03690","title":"Graph Neural Networks for Electricity Load Forecasting","created":"2025-07-04","cited_by_count":1,"area":null},{"id":"2509.12530","title":"Graph Homophily Booster: Rethinking the Role of Discrete Features on Heterophilic Graphs","created":"2025-09-16","cited_by_count":1,"area":null},{"id":"2512.06520","title":"Hierarchical geometric deep learning enables scalable analysis of molecular dynamics","created":"2025-12-06","cited_by_count":1,"area":null},{"id":"2512.18228","title":"Toward Efficient Testing of Graph Neural Networks via Test Input Prioritization","created":"2025-12-20","cited_by_count":1,"area":null},{"id":"2601.02806","title":"Topology-aware Pathological Consistency Matching for Weakly-Paired IHC Virtual Staining","created":"2026-01-06","cited_by_count":1,"area":null},{"id":"2602.07256","title":"Graph homophily booster: Reimagining the role of discrete features in heterophilic graph learning","created":"2026-02-06","cited_by_count":1,"area":null},{"id":"2602.15239","title":"Size-Transferability of Graph Transformers with Convolutional Positional Encodings","created":"2026-02-16","cited_by_count":1,"area":null},{"id":"2204.02625","title":"Bridging the Gap of AutoGraph between Academia and Industry: Analysing AutoGraph Challenge at KDD Cup 2020","created":"2022-04-06","cited_by_count":0,"area":null},{"id":"2207.01960","title":"A Safe Semi-supervised Graph Convolution Network","created":"2022-07-05","cited_by_count":0,"area":null},{"id":"2207.05887","title":"Tuning the Geometry of Graph Neural Networks","created":"2022-07-12","cited_by_count":0,"area":null},{"id":"2210.04277","title":"Boost Event-Driven Tactile Learning with Location Spiking Neurons","created":"2022-10-09","cited_by_count":0,"area":null},{"id":"2210.12257","title":"Efficient Automatic Machine Learning via Design Graphs","created":"2022-10-21","cited_by_count":0,"area":null},{"id":"2211.13015","title":"Semantics-Preserving Sketch Embedding for Face Generation","created":"2022-11-23","cited_by_count":0,"area":null},{"id":"2212.13709","title":"PersonaSAGE: A Multi-Persona Graph Neural Network","created":"2022-12-28","cited_by_count":0,"area":null},{"id":"2302.02128","title":"Interaction Order Prediction for Temporal Graphs","created":"2023-02-04","cited_by_count":0,"area":null},{"id":"2312.10943","title":"Model Stealing Attack against Graph Classification with Authenticity, Uncertainty and Diversity","created":"2023-12-18","cited_by_count":0,"area":null},{"id":"2404.07493","title":"Characterizing the Influence of Topology on Graph Learning Tasks","created":"2024-04-11","cited_by_count":0,"area":null},{"id":"2408.07624","title":"Battery GraphNets : Relational Learning for Lithium-ion Batteries(LiBs) Life Estimation","created":"2024-08-14","cited_by_count":0,"area":null},{"id":"2408.13248","title":"Foundational Model for Electron Micrograph Analysis: Instruction-Tuning Small-Scale Language-and-Vision Assistant for Enterprise Adoption","created":"2024-08-23","cited_by_count":0,"area":null},{"id":"2408.13621","title":"Preliminary Investigations of a Multi-Faceted Robust and Synergistic Approach in Semiconductor Electron Micrograph Analysis: Integrating Vision Transformers with Large Language and Multimodal Models","created":"2024-08-24","cited_by_count":0,"area":null},{"id":"2408.13661","title":"Hierarchical Network Fusion for Multi-Modal Electron Micrograph Representation Learning with Foundational Large Language Models","created":"2024-08-24","cited_by_count":0,"area":null},{"id":"2409.03767","title":"EMCNet : Graph-Nets for Electron Micrographs Classification","created":"2024-08-21","cited_by_count":0,"area":null},{"id":"2409.07463","title":"Multi-Modal Instruction-Tuning Small-Scale Language-and-Vision Assistant for Semiconductor Electron Micrograph Analysis","created":"2024-08-27","cited_by_count":0,"area":null},{"id":"2409.12244","title":"Sparks of Artificial General Intelligence(AGI) in Semiconductor Material Science: Early Explorations into the Next Frontier of Generative AI-Assisted Electron Micrograph Analysis","created":"2024-09-17","cited_by_count":0,"area":null}],"next_cursor":"100"}