{"total":38,"rows":[{"id":"2212.01026","title":"Spectral Feature Augmentation for Graph Contrastive Learning and Beyond","created":"2022-12-02","cited_by_count":49,"area":null},{"id":"2303.14474","title":"3Mformer: Multi-order Multi-mode Transformer for Skeletal Action Recognition","created":"2023-03-25","cited_by_count":40,"area":null},{"id":"2310.07365","title":"GraphControl: Adding Conditional Control to Universal Graph Pre-trained Models for Graph Domain Transfer Learning","created":"2023-10-11","cited_by_count":33,"area":null},{"id":"2302.10637","title":"A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy","created":"2023-02-21","cited_by_count":24,"area":null},{"id":"2211.00005","title":"Uncertainty-DTW for Time Series and Sequences","created":"2022-10-30","cited_by_count":21,"area":null},{"id":"2409.16670","title":"GraphLoRA: Structure-Aware Contrastive Low-Rank Adaptation for Cross-Graph Transfer Learning","created":"2024-09-25","cited_by_count":21,"area":null},{"id":"2306.09614","title":"HomoGCL: Rethinking Homophily in Graph Contrastive Learning","created":"2023-06-16","cited_by_count":18,"area":null},{"id":"2209.13964","title":"Graph Soft-Contrastive Learning via Neighborhood Ranking","created":"2022-09-28","cited_by_count":16,"area":null},{"id":"2212.01793","title":"kHGCN: Tree-likeness Modeling via Continuous and Discrete Curvature Learning","created":"2022-12-04","cited_by_count":14,"area":null},{"id":"2206.12933","title":"Wiener Graph Deconvolutional Network Improves Graph Self-Supervised Learning","created":"2022-06-26","cited_by_count":13,"area":null},{"id":"2305.05237","title":"Traffic Forecasting on New Roads Using Spatial Contrastive Pre-Training (SCPT)","created":"2023-05-09","cited_by_count":11,"area":null},{"id":"2402.03814","title":"Masked Graph Autoencoder with Non-discrete Bandwidths","created":"2024-02-06","cited_by_count":11,"area":null},{"id":"2407.19944","title":"Noise-Resilient Unsupervised Graph Representation Learning via Multi-Hop Feature Quality Estimation","created":"2024-07-29","cited_by_count":11,"area":null},{"id":"2310.18209","title":"Understanding and Mitigating Hyperbolic Dimensional Collapse in Graph Contrastive Learning","created":"2023-10-27","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":"2211.10929","title":"Towards Generalizable Graph Contrastive Learning: An Information Theory Perspective","created":"2022-11-20","cited_by_count":8,"area":null},{"id":"2307.13055","title":"MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning","created":"2023-07-24","cited_by_count":7,"area":null},{"id":"2206.12556","title":"Graph Component Contrastive Learning for Concept Relatedness Estimation","created":"2022-06-25","cited_by_count":6,"area":null},{"id":"2408.05087","title":"Bootstrap Latents of Nodes and Neighbors for Graph Self-Supervised Learning","created":"2024-08-09","cited_by_count":6,"area":null},{"id":"2411.01157","title":"Negative-Free Self-Supervised Gaussian Embedding of Graphs","created":"2024-11-02","cited_by_count":5,"area":null},{"id":"2310.13845","title":"Spectral-Aware Augmentation for Enhanced Graph Representation Learning","created":"2023-10-20","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":"2402.15680","title":"Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks","created":"2024-02-24","cited_by_count":3,"area":null},{"id":"2505.06282","title":"InfoNCE is a Free Lunch for Semantically guided Graph Contrastive Learning","created":"2025-05-07","cited_by_count":3,"area":null},{"id":"2212.05762","title":"Momentum Contrastive Pre-training for Question Answering","created":"2022-12-12","cited_by_count":2,"area":null},{"id":"2405.16224","title":"Negative as Positive: Enhancing Out-of-distribution Generalization for Graph Contrastive Learning","created":"2024-05-25","cited_by_count":2,"area":null},{"id":"2305.09729","title":"FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks","created":"2023-05-16","cited_by_count":1,"area":null},{"id":"2405.10642","title":"Hi-GMAE: Hierarchical Graph Masked Autoencoders","created":"2024-05-17","cited_by_count":1,"area":null},{"id":"2407.16726","title":"Topology Reorganized Graph Contrastive Learning with Mitigating Semantic Drift","created":"2024-07-23","cited_by_count":1,"area":null},{"id":"2502.13525","title":"AS-GCL: Asymmetric Spectral Augmentation on Graph Contrastive Learning","created":"2025-02-19","cited_by_count":1,"area":null},{"id":"2502.16233","title":"Graph Self-Supervised Learning with Learnable Structural and Positional Encodings","created":"2025-02-22","cited_by_count":1,"area":null},{"id":"2503.02397","title":"A Binary Classification Social Network Dataset for Graph Machine Learning","created":"2025-03-04","cited_by_count":1,"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":"2409.08010","title":"Multiplex Graph Contrastive Learning with Soft Negatives","created":"2024-09-12","cited_by_count":0,"area":null},{"id":"2506.20235","title":"Directed Link Prediction using GNN with Local and Global Feature Fusion","created":"2025-06-25","cited_by_count":0,"area":null},{"id":"2512.11359","title":"Attacking and Securing Community Detection: A Game-Theoretic Framework","created":"2025-12-12","cited_by_count":0,"area":null},{"id":"2605.03076","title":"AdNGCL: Adaptive Negative Scheduling for Graph Contrastive Learning","created":"2026-05-04","cited_by_count":0,"area":null},{"id":"2608.15084","title":"GATTA: Graph Active Learning with Test-Time Augmentation","created":"2026-08-15","cited_by_count":0,"area":null}],"next_cursor":null}