{"total":21,"rows":[{"id":"2311.16534","title":"Graph Prompt Learning: A Comprehensive Survey and Beyond","created":"2023-11-28","cited_by_count":61,"area":null},{"id":"2406.05346","title":"ProG: A Graph Prompt Learning Benchmark","created":"2024-06-08","cited_by_count":29,"area":null},{"id":"2309.16014","title":"Graph-level Representation Learning with Joint-Embedding Predictive Architectures","created":"2023-09-27","cited_by_count":22,"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":"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":"2412.03864","title":"Training MLPs on Graphs without Supervision","created":"2024-12-05","cited_by_count":8,"area":null},{"id":"2402.01440","title":"A Survey of Few-Shot Learning on Graphs: from Meta-Learning to Pre-Training and Prompt Learning","created":"2024-02-02","cited_by_count":6,"area":null},{"id":"2304.03724","title":"GeoTMI:Predicting quantum chemical property with easy-to-obtain geometry via positional denoising","created":"2023-03-28","cited_by_count":5,"area":null},{"id":"2403.05064","title":"Unsupervised Graph Neural Architecture Search with Disentangled Self-supervision","created":"2024-03-08","cited_by_count":5,"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":"2507.19526","title":"Quantizing Text-attributed Graphs for Semantic-Structural Integration","created":"2025-07-20","cited_by_count":4,"area":null},{"id":"2309.02304","title":"Graph Self-Contrast Representation Learning","created":"2023-09-05","cited_by_count":1,"area":null},{"id":"2402.08918","title":"SimMLP: Training MLPs on Graphs without Supervision","created":"2024-02-14","cited_by_count":0,"area":null},{"id":"2402.15270","title":"Smoothed Graph Contrastive Learning via Seamless Proximity Integration","created":"2024-02-23","cited_by_count":0,"area":null},{"id":"2407.07639","title":"Explaining Graph Neural Networks for Node Similarity on Graphs","created":"2024-07-10","cited_by_count":0,"area":null},{"id":"2506.23469","title":"Reconciling Attribute and Structural Anomalies for Improved Graph Anomaly Detection","created":"2025-06-30","cited_by_count":0,"area":null},{"id":"2509.22468","title":"Learning the Neighborhood: Contrast-Free Multimodal Self-Supervised Molecular Graph Pretraining","created":"2025-09-26","cited_by_count":0,"area":null},{"id":"2511.07170","title":"On Stealing Graph Neural Network Models","created":"2025-11-10","cited_by_count":0,"area":null},{"id":"2512.13235","title":"CORE: Contrastive Masked Feature Reconstruction on Graphs","created":"2025-12-15","cited_by_count":0,"area":null},{"id":"2604.00399","title":"A Cross-graph Tuning-free GNN Prompting Framework","created":"2026-04-01","cited_by_count":0,"area":null},{"id":"2609.25650","title":"Decoupling Disease, Covariates, and Individual Variability: A Unified Disentanglement Framework for Medical Image Classification","created":"2026-09-22","cited_by_count":0,"area":null}],"next_cursor":null}