{"total":23,"rows":[{"id":"2202.10156","title":"1-WL Expressiveness Is (Almost) All You Need","created":"2022-02-21","cited_by_count":15,"area":null},{"id":"2212.08689","title":"TopoImb: Toward Topology-level Imbalance in Learning from Graphs","created":"2022-12-16","cited_by_count":12,"area":null},{"id":"2310.01794","title":"GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking","created":"2023-10-03","cited_by_count":11,"area":null},{"id":"2409.17687","title":"Graph Edit Distance with General Costs Using Neural Set Divergence","created":"2024-09-26","cited_by_count":11,"area":null},{"id":"2205.10914","title":"Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited","created":"2022-05-22","cited_by_count":9,"area":null},{"id":"2303.07669","title":"AutoTransfer: AutoML with Knowledge Transfer -- An Application to Graph Neural Networks","created":"2023-03-14","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":"2301.05860","title":"State of the Art and Potentialities of Graph-level Learning","created":"2023-01-14","cited_by_count":6,"area":null},{"id":"2405.02795","title":"Graph as Point Set","created":"2024-05-05","cited_by_count":4,"area":null},{"id":"2402.04435","title":"PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection","created":"2024-02-06","cited_by_count":3,"area":null},{"id":"2501.08850","title":"Graph Counterfactual Explainable AI via Latent Space Traversal","created":"2025-01-15","cited_by_count":3,"area":null},{"id":"2601.07419","title":"Position: Don't be Afraid of Over-Smoothing And Over-Squashing","created":"2026-01-12","cited_by_count":2,"area":null},{"id":"2501.13456","title":"KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks","created":"2025-01-23","cited_by_count":1,"area":null},{"id":"2205.15555","title":"Graph-level Neural Networks: Current Progress and Future Directions","created":"2022-05-31","cited_by_count":0,"area":null},{"id":"2211.10579","title":"Tired of Over-smoothing? Stress Graph Drawing Is All You Need!","created":"2022-11-19","cited_by_count":0,"area":null},{"id":"2304.10045","title":"ID-MixGCL: Identity Mixup for Graph Contrastive Learning","created":"2023-04-20","cited_by_count":0,"area":null},{"id":"2307.05775","title":"Weisfeiler and Leman Go Measurement Modeling: Probing the Validity of the WL Test","created":"2023-07-11","cited_by_count":0,"area":null},{"id":"2402.05885","title":"EUGENE: Explainable Structure-aware Graph Edit Distance Estimation with Generalized Edit Costs","created":"2024-02-08","cited_by_count":0,"area":null},{"id":"2408.05474","title":"A Structural Feature-Based Approach for Comprehensive Graph Classification","created":"2024-08-10","cited_by_count":0,"area":null},{"id":"2502.01693","title":"Predicting Steady-State Behavior in Complex Networks with Graph Neural Networks","created":"2025-02-02","cited_by_count":0,"area":null},{"id":"2509.09107","title":"CryptGNN: Enabling Secure Inference for Graph Neural Networks","created":"2025-09-11","cited_by_count":0,"area":null},{"id":"2601.15474","title":"BadImplant: Injection-based Multi-Targeted Graph Backdoor Attack","created":"2026-01-21","cited_by_count":0,"area":null},{"id":"2610.15020","title":"PATTERN Can Be Solved from Memory: Generator-Aware Baselines for Synthetic Node Classification","created":"2026-10-10","cited_by_count":0,"area":null}],"next_cursor":null}