{"total":105,"rows":[{"id":"2205.10803","title":"GraphMAE: Self-Supervised Masked Graph Autoencoders","created":"2022-05-22","cited_by_count":448,"area":null},{"id":"2304.04779","title":"GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner","created":"2023-04-10","cited_by_count":132,"area":null},{"id":"2306.13089","title":"GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning","created":"2023-05-28","cited_by_count":70,"area":null},{"id":"2202.08871","title":"Graph Data Augmentation for Graph Machine Learning: A Survey","created":"2022-02-17","cited_by_count":62,"area":null},{"id":"2306.04979","title":"CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification","created":"2023-06-08","cited_by_count":46,"area":null},{"id":"2210.02330","title":"Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum","created":"2022-10-05","cited_by_count":43,"area":null},{"id":"2310.16520","title":"Towards Self-Interpretable Graph-Level Anomaly Detection","created":"2023-10-25","cited_by_count":41,"area":null},{"id":"2311.15317","title":"Generalized Graph Prompt: Toward a Unification of Pre-Training and Downstream Tasks on Graphs","created":"2023-11-26","cited_by_count":39,"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":"2210.16484","title":"A Systematic Survey of Chemical Pre-trained Models","created":"2022-10-29","cited_by_count":34,"area":null},{"id":"2210.10462","title":"Self-supervised Heterogeneous Graph Pre-training Based on Structural Clustering","created":"2022-10-19","cited_by_count":30,"area":null},{"id":"2406.05346","title":"ProG: A Graph Prompt Learning Benchmark","created":"2024-06-08","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":"2404.00225","title":"Heterogeneous Contrastive Learning for Foundation Models and Beyond","created":"2024-03-30","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":"2302.07491","title":"Self-Supervised Temporal Graph learning with Temporal and Structural Intensity Alignment","created":"2023-02-15","cited_by_count":25,"area":null},{"id":"2306.08194","title":"Learning on Graphs under Label Noise","created":"2023-06-14","cited_by_count":22,"area":null},{"id":"2402.07225","title":"Rethinking Graph Masked Autoencoders through Alignment and Uniformity","created":"2024-02-11","cited_by_count":22,"area":null},{"id":"2202.02989","title":"Graph Self-supervised Learning with Accurate Discrepancy Learning","created":"2022-02-07","cited_by_count":21,"area":null},{"id":"2205.11332","title":"ImGCL: Revisiting Graph Contrastive Learning on Imbalanced Node Classification","created":"2022-05-23","cited_by_count":21,"area":null},{"id":"2410.10365","title":"SpeGCL: Self-supervised Graph Spectrum Contrastive Learning without Positive Samples","created":"2024-10-14","cited_by_count":20,"area":null},{"id":"2205.09802","title":"Label-invariant Augmentation for Semi-Supervised Graph Classification","created":"2022-05-19","cited_by_count":19,"area":null},{"id":"2208.09905","title":"MentorGNN: Deriving Curriculum for Pre-Training GNNs","created":"2022-08-21","cited_by_count":18,"area":null},{"id":"2306.09614","title":"HomoGCL: Rethinking Homophily in Graph Contrastive Learning","created":"2023-06-16","cited_by_count":18,"area":null},{"id":"2406.11945","title":"GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models","created":"2024-06-17","cited_by_count":17,"area":null},{"id":"2209.13964","title":"Graph Soft-Contrastive Learning via Neighborhood Ranking","created":"2022-09-28","cited_by_count":16,"area":null},{"id":"2410.20105","title":"FedSSP: Federated Graph Learning with Spectral Knowledge and Personalized Preference","created":"2024-10-26","cited_by_count":16,"area":null},{"id":"2311.01038","title":"Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks","created":"2023-11-02","cited_by_count":14,"area":null},{"id":"2311.04245","title":"GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks","created":"2023-11-07","cited_by_count":14,"area":null},{"id":"2311.11009","title":"Joyful: Joint Modality Fusion and Graph Contrastive Learning for Multimodal Emotion Recognition","created":"2023-11-18","cited_by_count":14,"area":null},{"id":"2406.12052","title":"UniGLM: Training One Unified Language Model for Text-Attributed Graph Embedding","created":"2024-06-17","cited_by_count":14,"area":null},{"id":"2205.13700","title":"ES-GNN: Generalizing Graph Neural Networks Beyond Homophily with Edge Splitting","created":"2022-05-27","cited_by_count":13,"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":"2306.10683","title":"Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation","created":"2023-06-19","cited_by_count":13,"area":null},{"id":"2306.13210","title":"Directional diffusion models for graph representation learning","created":"2023-06-22","cited_by_count":13,"area":"diffusion"},{"id":"2402.10434","title":"Parametric Augmentation for Time Series Contrastive Learning","created":"2024-02-16","cited_by_count":12,"area":null},{"id":"2212.07035","title":"MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning","created":"2022-12-14","cited_by_count":11,"area":null},{"id":"2505.16130","title":"Generative Graph Pattern Machine","created":"2025-05-22","cited_by_count":11,"area":null},{"id":"2304.01507","title":"RARE: Robust Masked Graph Autoencoder","created":"2023-04-04","cited_by_count":10,"area":null},{"id":"2312.02203","title":"Learning High-Order Relationships of Brain Regions","created":"2023-12-02","cited_by_count":10,"area":null},{"id":"2405.16435","title":"Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning","created":"2024-05-26","cited_by_count":10,"area":null},{"id":"2301.13340","title":"Affinity Uncertainty-based Hard Negative Mining in Graph Contrastive Learning","created":"2023-01-31","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":"2207.07650","title":"Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model","created":"2022-07-14","cited_by_count":8,"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":"2302.02909","title":"Spectral Augmentations for Graph Contrastive Learning","created":"2023-02-06","cited_by_count":8,"area":null},{"id":"2305.09938","title":"Mastering Long-Tail Complexity on Graphs: Characterization, Learning, and Generalization","created":"2023-05-17","cited_by_count":8,"area":null},{"id":"2403.03483","title":"A Teacher-Free Graph Knowledge Distillation Framework with Dual Self-Distillation","created":"2024-03-06","cited_by_count":8,"area":"distill"},{"id":"2211.03710","title":"Graph Contrastive Learning with Implicit Augmentations","created":"2022-11-07","cited_by_count":7,"area":null},{"id":"2305.10673","title":"Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs","created":"2023-05-18","cited_by_count":7,"area":null},{"id":"2306.03355","title":"BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs","created":"2023-06-06","cited_by_count":7,"area":null},{"id":"2404.15806","title":"Where to Mask: Structure-Guided Masking for Graph Masked Autoencoders","created":"2024-04-24","cited_by_count":7,"area":null},{"id":"2407.14732","title":"Meta-GPS++: Enhancing Graph Meta-Learning with Contrastive Learning and Self-Training","created":"2024-07-20","cited_by_count":7,"area":null},{"id":"2310.10064","title":"Shape-aware Graph Spectral Learning","created":"2023-10-16","cited_by_count":6,"area":null},{"id":"2311.02798","title":"Multi-channel learning for integrating structural hierarchies into context-dependent molecular representation","created":"2023-11-05","cited_by_count":6,"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":"2307.01053","title":"ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning","created":"2023-07-03","cited_by_count":5,"area":null},{"id":"2411.16787","title":"Contrastive Multi-graph Learning with Neighbor Hierarchical Sifting for Semi-supervised Text Classification","created":"2024-11-25","cited_by_count":5,"area":null},{"id":"2302.02369","title":"Deep Graph-Level Clustering Using Pseudo-Label-Guided Mutual Information Maximization Network","created":"2023-02-05","cited_by_count":3,"area":null},{"id":"2309.14277","title":"SINCERE: Supervised Information Noise-Contrastive Estimation REvisited","created":"2023-09-25","cited_by_count":3,"area":null},{"id":"2310.03977","title":"Perfect Alignment May be Poisonous to Graph Contrastive Learning","created":"2023-10-06","cited_by_count":3,"area":null},{"id":"2409.02714","title":"MOOSS: Mask-Enhanced Temporal Contrastive Learning for Smooth State Evolution in Visual Reinforcement Learning","created":"2024-09-02","cited_by_count":3,"area":"deeprl"},{"id":"2504.12011","title":"Balancing Graph Embedding Smoothness in Self-Supervised Learning via Information-Theoretic Decomposition","created":"2025-04-16","cited_by_count":3,"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":"2302.09532","title":"Pseudo Contrastive Learning for Graph-based Semi-supervised Learning","created":"2023-02-19","cited_by_count":2,"area":null},{"id":"2310.14525","title":"Graph Ranking Contrastive Learning: A Extremely Simple yet Efficient Method","created":"2023-10-23","cited_by_count":2,"area":null},{"id":"2402.08023","title":"UGMAE: A Unified Framework for Graph Masked Autoencoders","created":"2024-02-12","cited_by_count":2,"area":null},{"id":"2403.14340","title":"Exploring Task Unification in Graph Representation Learning via Generative Approach","created":"2024-03-21","cited_by_count":2,"area":null},{"id":"2410.04765","title":"Molecular topological deep learning for polymer property prediction","created":"2024-10-07","cited_by_count":2,"area":null},{"id":"2502.08949","title":"DICE: Device-level Integrated Circuits Encoder with Graph Contrastive Pretraining","created":"2025-02-13","cited_by_count":2,"area":null},{"id":"2505.21285","title":"Learnable Kernel Density Estimation for Graphs and Its Application to Graph-Level Anomaly Detection","created":"2025-05-27","cited_by_count":2,"area":null},{"id":"2209.07699","title":"Graph Contrastive Learning with Cross-view Reconstruction","created":"2022-09-16","cited_by_count":1,"area":null},{"id":"2303.08958","title":"NESS: Node Embeddings from Static SubGraphs","created":"2023-03-15","cited_by_count":1,"area":null},{"id":"2309.00957","title":"Visual-Kinematics Graph Learning for Procedure-agnostic Instrument Tip Segmentation in Robotic Surgeries","created":"2023-09-02","cited_by_count":1,"area":null},{"id":"2311.03976","title":"Topology Only Pre-Training: Towards Generalised Multi-Domain Graph Models","created":"2023-11-07","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":"2406.08709","title":"Introducing Diminutive Causal Structure into Graph Representation Learning","created":"2024-06-13","cited_by_count":1,"area":null},{"id":"2408.13471","title":"Disentangled Generative Graph Representation Learning","created":"2024-08-24","cited_by_count":1,"area":null},{"id":"2410.10089","title":"PromptGCN: Bridging Subgraph Gaps in Lightweight GCNs","created":"2024-10-14","cited_by_count":1,"area":null},{"id":"2410.10241","title":"Revisiting Graph Autoencoders as Implicit Contrastive Learners","created":"2024-10-14","cited_by_count":1,"area":null},{"id":"2410.12657","title":"Explanation-Preserving Augmentation for Semi-Supervised Graph Representation Learning","created":"2024-10-16","cited_by_count":1,"area":null},{"id":"2412.11652","title":"SE-GCL: An Event-Based Simple and Effective Graph Contrastive Learning for Text Representation","created":"2024-12-16","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":"2505.04956","title":"Graffe: Graph Representation Learning via Diffusion Probabilistic Models","created":"2025-05-08","cited_by_count":1,"area":"diffusion"},{"id":"2505.08168","title":"Exploiting Text Semantics for Few and Zero Shot Node Classification on Text-attributed Graph","created":"2025-05-13","cited_by_count":1,"area":null},{"id":"2505.19020","title":"HGCL: Hierarchical Graph Contrastive Learning for User-Item Recommendation","created":"2025-05-25","cited_by_count":1,"area":null},{"id":"2507.06366","title":"DecoyDB: A Dataset for Graph Contrastive Learning in Protein-Ligand Binding Affinity Prediction","created":"2025-07-08","cited_by_count":1,"area":null},{"id":"2605.17285","title":"UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models","created":"2026-05-17","cited_by_count":1,"area":null},{"id":"2301.08496","title":"Introducing Expertise Logic into Graph Representation Learning from A Causal Perspective","created":"2023-01-20","cited_by_count":0,"area":null},{"id":"2301.12063","title":"HAT-GAE: Self-Supervised Graph Auto-encoders with Hierarchical Adaptive Masking and Trainable Corruption","created":"2023-01-28","cited_by_count":0,"area":null},{"id":"2303.08644","title":"Feature propagation as self-supervision signals on graphs","created":"2023-03-15","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":"2309.01503","title":"Layer-wise training for self-supervised learning on graphs","created":"2023-09-04","cited_by_count":0,"area":null},{"id":"2401.10590","title":"Adversarial Robustness of Link Sign Prediction in Signed Graphs","created":"2024-01-19","cited_by_count":0,"area":null},{"id":"2405.14742","title":"HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning","created":"2024-05-23","cited_by_count":0,"area":null},{"id":"2406.17517","title":"Preserving Node Distinctness in Graph Autoencoders via Similarity Distillation","created":"2024-06-25","cited_by_count":0,"area":"distill"},{"id":"2409.08010","title":"Multiplex Graph Contrastive Learning with Soft Negatives","created":"2024-09-12","cited_by_count":0,"area":null},{"id":"2410.03396","title":"GraphCroc: Cross-Correlation Autoencoder for Graph Structural Reconstruction","created":"2024-10-04","cited_by_count":0,"area":null},{"id":"2506.20362","title":"Self-Supervised Graph Learning via Spectral Bootstrapping and Laplacian-Based Augmentations","created":"2025-06-25","cited_by_count":0,"area":null}],"next_cursor":"100"}