{"total":106,"rows":[{"id":"2205.10803","title":"GraphMAE: Self-Supervised Masked Graph Autoencoders","created":"2022-05-22","cited_by_count":448,"area":null},{"id":"2103.00111","title":"Graph Self-Supervised Learning: A Survey","created":"2021-02-27","cited_by_count":289,"area":null},{"id":"2106.07594","title":"Graph Contrastive Learning Automated","created":"2021-06-10","cited_by_count":287,"area":null},{"id":"2102.10757","title":"Self-Supervised Learning of Graph Neural Networks: A Unified Review","created":"2021-02-22","cited_by_count":184,"area":null},{"id":"2307.01504","title":"All in One: Multi-task Prompting for Graph Neural Networks","created":"2023-07-04","cited_by_count":148,"area":null},{"id":"2105.07342","title":"Self-supervised Learning on Graphs: Contrastive, Generative,or Predictive","created":"2021-05-16","cited_by_count":136,"area":null},{"id":"2102.05034","title":"SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks","created":"2021-02-09","cited_by_count":110,"area":null},{"id":"2209.15240","title":"Universal Prompt Tuning for Graph Neural Networks","created":"2022-09-30","cited_by_count":100,"area":null},{"id":"2402.02216","title":"Position: Graph Foundation Models are Already Here","created":"2024-02-03","cited_by_count":86,"area":null},{"id":"2103.12608","title":"DIG: A Turnkey Library for Diving into Graph Deep Learning Research","created":"2021-03-23","cited_by_count":76,"area":null},{"id":"2108.12055","title":"Towards Self-Explainable Graph Neural Network","created":"2021-08-26","cited_by_count":75,"area":null},{"id":"2106.04051","title":"Graph-MLP: Node Classification without Message Passing in Graph","created":"2021-06-08","cited_by_count":73,"area":null},{"id":"2104.14210","title":"FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning","created":"2021-04-29","cited_by_count":68,"area":null},{"id":"2201.00232","title":"Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels","created":"2022-01-01","cited_by_count":63,"area":null},{"id":"2206.03426","title":"Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage","created":"2022-06-07","cited_by_count":61,"area":null},{"id":"2207.04869","title":"Graph-based Molecular Representation Learning","created":"2022-07-08","cited_by_count":51,"area":null},{"id":"2106.05470","title":"Automated Self-Supervised Learning for Graphs","created":"2021-06-10","cited_by_count":50,"area":null},{"id":"2502.02017","title":"Multi-Domain Graph Foundation Models: Robust Knowledge Transfer via Topology Alignment","created":"2025-02-04","cited_by_count":42,"area":null},{"id":"2210.00643","title":"Spectral Augmentation for Self-Supervised Learning on Graphs","created":"2022-10-02","cited_by_count":39,"area":null},{"id":"2106.11133","title":"GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction","created":"2021-06-21","cited_by_count":36,"area":null},{"id":"2108.11022","title":"Tree Decomposed Graph Neural Network","created":"2021-08-25","cited_by_count":35,"area":null},{"id":"2302.12449","title":"SGL-PT: A Strong Graph Learner with Graph Prompt Tuning","created":"2023-02-24","cited_by_count":35,"area":null},{"id":"2206.14116","title":"SSL-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous Driving","created":"2022-06-28","cited_by_count":32,"area":null},{"id":"2412.16441","title":"Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees","created":"2024-12-21","cited_by_count":32,"area":null},{"id":"2104.07917","title":"Hop-Count Based Self-Supervised Anomaly Detection on Attributed Networks","created":"2021-04-16","cited_by_count":31,"area":null},{"id":"2107.08765","title":"Adaptive Transfer Learning on Graph Neural Networks","created":"2021-07-19","cited_by_count":31,"area":null},{"id":"2210.00102","title":"MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization","created":"2022-09-30","cited_by_count":31,"area":null},{"id":"2210.03801","title":"Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative","created":"2022-10-07","cited_by_count":29,"area":null},{"id":"2201.01702","title":"Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations","created":"2022-01-04","cited_by_count":28,"area":null},{"id":"2201.02534","title":"MGAE: Masked Autoencoders for Self-Supervised Learning on Graphs","created":"2022-01-07","cited_by_count":28,"area":null},{"id":"2208.08723","title":"Disentangled Contrastive Learning for Social Recommendation","created":"2022-08-18","cited_by_count":27,"area":null},{"id":"2405.11868","title":"Towards Graph Contrastive Learning: A Survey and Beyond","created":"2024-05-20","cited_by_count":26,"area":null},{"id":"2106.15762","title":"Curvature Graph Neural Network","created":"2021-06-30","cited_by_count":24,"area":null},{"id":"2202.11245","title":"Exploring Edge Disentanglement for Node Classification","created":"2022-02-23","cited_by_count":23,"area":null},{"id":"2209.14930","title":"Graph Anomaly Detection with Graph Neural Networks: Current Status and Challenges","created":"2022-09-29","cited_by_count":23,"area":null},{"id":"2312.14535","title":"ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly Detection","created":"2023-12-22","cited_by_count":23,"area":null},{"id":"2202.00961","title":"Modularity-Aware Graph Autoencoders for Joint Community Detection and Link Prediction","created":"2022-02-02","cited_by_count":22,"area":null},{"id":"2202.08333","title":"Self-Supervised Representation Learning via Latent Graph Prediction","created":"2022-02-16","cited_by_count":22,"area":null},{"id":"2308.16375","title":"A Survey on Privacy in Graph Neural Networks: Attacks, Preservation, and Applications","created":"2023-08-31","cited_by_count":22,"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":"2211.06545","title":"Self-Supervised Graph Structure Refinement for Graph Neural Networks","created":"2022-11-12","cited_by_count":20,"area":null},{"id":"2103.08827","title":"Semi-Supervised Graph-to-Graph Translation","created":"2021-03-16","cited_by_count":18,"area":null},{"id":"2108.03388","title":"Jointly Attacking Graph Neural Network and its Explanations","created":"2021-08-07","cited_by_count":18,"area":null},{"id":"2402.00447","title":"A Survey of Data-Efficient Graph Learning","created":"2024-02-01","cited_by_count":18,"area":null},{"id":"2503.00750","title":"Edge Prompt Tuning for Graph Neural Networks","created":"2025-03-02","cited_by_count":18,"area":null},{"id":"2108.10733","title":"Graph Neural Networks: Methods, Applications, and Opportunities","created":"2021-08-24","cited_by_count":16,"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":"2209.06560","title":"Graph Contrastive Learning with Personalized Augmentation","created":"2022-09-14","cited_by_count":14,"area":null},{"id":"2201.04437","title":"Multi-task Joint Strategies of Self-supervised Representation Learning on Biomedical Networks for Drug Discovery","created":"2022-01-12","cited_by_count":13,"area":null},{"id":"2211.14394","title":"Link Prediction with Non-Contrastive Learning","created":"2022-11-25","cited_by_count":11,"area":null},{"id":"2206.03601","title":"Decoupled Self-supervised Learning for Non-Homophilous Graphs","created":"2022-06-07","cited_by_count":10,"area":null},{"id":"2402.02464","title":"A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer","created":"2024-02-04","cited_by_count":10,"area":null},{"id":"2105.10862","title":"Hypergraph Pre-training with Graph Neural Networks","created":"2021-05-23","cited_by_count":9,"area":null},{"id":"2310.15523","title":"Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning","created":"2023-10-24","cited_by_count":9,"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":"2202.00097","title":"Self-supervised Graphs for Audio Representation Learning with Limited Labeled Data","created":"2022-01-31","cited_by_count":8,"area":null},{"id":"2207.11996","title":"Generative Subgraph Contrast for Self-Supervised Graph Representation Learning","created":"2022-07-25","cited_by_count":8,"area":null},{"id":"2210.04672","title":"Exploiting map information for self-supervised learning in motion forecasting","created":"2022-10-10","cited_by_count":8,"area":null},{"id":"2310.17394","title":"PSP: Pre-Training and Structure Prompt Tuning for Graph Neural Networks","created":"2023-10-26","cited_by_count":8,"area":null},{"id":"2305.09887","title":"Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation","created":"2023-05-17","cited_by_count":7,"area":null},{"id":"2403.01400","title":"Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks","created":"2024-03-03","cited_by_count":7,"area":null},{"id":"2405.04245","title":"Exploring Correlations of Self-Supervised Tasks for Graphs","created":"2024-05-07","cited_by_count":7,"area":null},{"id":"2103.00771","title":"Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning","created":"2021-03-01","cited_by_count":6,"area":null},{"id":"2411.17063","title":"Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning","created":"2024-11-26","cited_by_count":6,"area":null},{"id":"2411.17676","title":"Instance-Aware Graph Prompt Learning","created":"2024-11-26","cited_by_count":6,"area":null},{"id":"2109.07371","title":"Self-learn to Explain Siamese Networks Robustly","created":"2021-09-15","cited_by_count":5,"area":null},{"id":"2205.15746","title":"Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning","created":"2022-05-31","cited_by_count":5,"area":null},{"id":"2212.04214","title":"Scientific Paper Extractive Summarization Enhanced by Citation Graphs","created":"2022-12-08","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":"2510.22451","title":"GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks","created":"2025-10-25","cited_by_count":5,"area":null},{"id":"2201.10069","title":"Link Prediction with Contextualized Self-Supervision","created":"2022-01-25","cited_by_count":4,"area":null},{"id":"2202.03341","title":"Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences","created":"2022-02-07","cited_by_count":4,"area":null},{"id":"2208.03819","title":"Cross-Skeleton Interaction Graph Aggregation Network for Representation Learning of Mouse Social Behaviour","created":"2022-08-07","cited_by_count":4,"area":null},{"id":"2308.03271","title":"Local Structure-aware Graph Contrastive Representation Learning","created":"2023-08-07","cited_by_count":4,"area":null},{"id":"2406.15044","title":"From Overfitting to Robustness: Quantity, Quality, and Variety Oriented Negative Sample Selection in Graph Contrastive Learning","created":"2024-06-21","cited_by_count":4,"area":null},{"id":"2502.19252","title":"GraphBridge: Towards Arbitrary Transfer Learning in GNNs","created":"2025-02-26","cited_by_count":4,"area":null},{"id":"2105.04493","title":"Graph Feature Gating Networks","created":"2021-05-10","cited_by_count":3,"area":null},{"id":"2111.10772","title":"Network representation learning: A macro and micro view","created":"2021-11-21","cited_by_count":3,"area":null},{"id":"2310.12169","title":"Enhanced Graph Neural Networks with Ego-Centric Spectral Subgraph Embeddings Augmentation","created":"2023-10-10","cited_by_count":3,"area":null},{"id":"2403.07040","title":"All in One: Multi-Task Prompting for Graph Neural Networks (Extended Abstract)","created":"2024-03-11","cited_by_count":3,"area":null},{"id":"2410.21749","title":"Reliable and Compact Graph Fine-tuning via GraphSparse Prompting","created":"2024-10-29","cited_by_count":3,"area":null},{"id":"2506.08326","title":"Graph Prompting for Graph Learning Models: Recent Advances and Future Directions","created":"2025-06-10","cited_by_count":3,"area":null},{"id":"2112.07934","title":"Graph Representation Learning via Contrasting Cluster Assignments","created":"2021-12-15","cited_by_count":2,"area":null},{"id":"2208.06743","title":"Enhancing Graph Contrastive Learning with Node Similarity","created":"2022-08-13","cited_by_count":2,"area":null},{"id":"2302.02317","title":"Adversarial Learning Data Augmentation for Graph Contrastive Learning in Recommendation","created":"2023-02-05","cited_by_count":2,"area":null},{"id":"2303.07778","title":"GANN: Graph Alignment Neural Network for Semi-Supervised Learning","created":"2023-03-14","cited_by_count":2,"area":null},{"id":"2103.03116","title":"Universal Representation for Code","created":"2021-03-04","cited_by_count":1,"area":null},{"id":"2209.04218","title":"Self-supervised Learning for Heterogeneous Graph via Structure Information based on Metapath","created":"2022-09-09","cited_by_count":1,"area":null},{"id":"2212.04365","title":"Alleviating neighbor bias: augmenting graph self-supervise learning with structural equivalent positive samples","created":"2022-12-08","cited_by_count":1,"area":null},{"id":"2212.04725","title":"Augmenting Knowledge Transfer across Graphs","created":"2022-12-09","cited_by_count":1,"area":null},{"id":"2301.04824","title":"A Network Science perspective of Graph Convolutional Networks: A survey","created":"2023-01-12","cited_by_count":1,"area":null},{"id":"2408.14520","title":"Towards Graph Prompt Learning: A Survey and Beyond","created":"2024-08-26","cited_by_count":1,"area":null},{"id":"2504.10925","title":"Transfer Learning for Temporal Link Prediction","created":"2025-04-15","cited_by_count":1,"area":null},{"id":"2506.18194","title":"Joint Embedding Predictive Architecture for self-supervised pretraining on polymer molecular graphs","created":"2025-06-22","cited_by_count":1,"area":null},{"id":"2508.02600","title":"Adaptive Riemannian Graph Neural Networks","created":"2025-08-04","cited_by_count":1,"area":null},{"id":"2201.12843","title":"Graph Representation Learning via Aggregation Enhancement","created":"2022-01-30","cited_by_count":0,"area":null},{"id":"2306.03506","title":"Subgraph Networks Based Contrastive Learning","created":"2023-06-06","cited_by_count":0,"area":null},{"id":"2306.04004","title":"Randomized Schur Complement Views for Graph Contrastive Learning","created":"2023-06-06","cited_by_count":0,"area":null},{"id":"2307.00859","title":"CardiGraphormer: Unveiling the Power of Self-Supervised Learning in Revolutionizing Drug Discovery","created":"2023-07-03","cited_by_count":0,"area":null},{"id":"2405.19033","title":"CiliaGraph: Enabling Expression-enhanced Hyper-Dimensional Computation in Ultra-Lightweight and One-Shot Graph Classification on Edge","created":"2024-05-29","cited_by_count":0,"area":null}],"next_cursor":"100"}