{"total":35,"rows":[{"id":"2402.08170","title":"LLaGA: Large Language and Graph Assistant","created":"2024-02-13","cited_by_count":181,"area":null},{"id":"2402.02216","title":"Position: Graph Foundation Models are Already Here","created":"2024-02-03","cited_by_count":86,"area":null},{"id":"2411.06070","title":"GFT: Graph Foundation Model with Transferable Tree Vocabulary","created":"2024-11-09","cited_by_count":85,"area":null},{"id":"2408.14512","title":"LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token Embeddings","created":"2024-08-25","cited_by_count":61,"area":null},{"id":"2210.05801","title":"Linkless Link Prediction via Relational Distillation","created":"2022-10-11","cited_by_count":39,"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":"2310.00800","title":"GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation","created":"2023-10-01","cited_by_count":31,"area":null},{"id":"2211.12875","title":"A Survey of Deep Graph Clustering: Taxonomy, Challenge, Application, and Open Resource","created":"2022-11-23","cited_by_count":26,"area":null},{"id":"2308.14522","title":"Graph Meets LLMs: Towards Large Graph Models","created":"2023-08-28","cited_by_count":20,"area":null},{"id":"2412.08847","title":"MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation","created":"2024-12-12","cited_by_count":18,"area":null},{"id":"2411.06427","title":"UniGAD: Unifying Multi-level Graph Anomaly Detection","created":"2024-11-10","cited_by_count":14,"area":null},{"id":"2601.22384","title":"Graph is a Substrate Across Data Modalities","created":"2026-01-29","cited_by_count":14,"area":null},{"id":"2412.00315","title":"One Model for One Graph: A New Perspective for Pretraining with Cross-domain Graphs","created":"2024-11-30","cited_by_count":12,"area":null},{"id":"2211.14394","title":"Link Prediction with Non-Contrastive Learning","created":"2022-11-25","cited_by_count":11,"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":"2502.15054","title":"GiGL: Large-Scale Graph Neural Networks at Snapchat","created":"2025-02-20","cited_by_count":8,"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":"2407.16234","title":"A Multi-view Mask Contrastive Learning Graph Convolutional Neural Network for Age Estimation","created":"2024-07-23","cited_by_count":7,"area":null},{"id":"2510.16885","title":"UniGTE: Unified Graph-Text Encoding for Zero-Shot Generalization across Graph Tasks and Domains","created":"2025-10-19","cited_by_count":7,"area":null},{"id":"2306.06936","title":"CARL-G: Clustering-Accelerated Representation Learning on Graphs","created":"2023-06-12","cited_by_count":6,"area":null},{"id":"2401.06595","title":"Every Node is Different: Dynamically Fusing Self-Supervised Tasks for Attributed Graph Clustering","created":"2024-01-12","cited_by_count":6,"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":"2404.08660","title":"How Does Message Passing Improve Collaborative Filtering?","created":"2024-03-27","cited_by_count":5,"area":null},{"id":"2409.14682","title":"Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems","created":"2024-09-23","cited_by_count":3,"area":null},{"id":"2505.21811","title":"Revisiting Self-attention for Cross-domain Sequential Recommendation","created":"2025-05-27","cited_by_count":3,"area":null},{"id":"2602.12373","title":"Policy4OOD: A Knowledge-Guided World Model for Policy Intervention Simulation against the Opioid Overdose Crisis","created":"2026-02-12","cited_by_count":3,"area":null},{"id":"2606.17667","title":"Handling Feature Heterogeneity with Learnable Graph Patches","created":"2026-06-16","cited_by_count":3,"area":null},{"id":"2503.01488","title":"InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization","created":"2025-03-03","cited_by_count":2,"area":null},{"id":"2502.01684","title":"Predict, Cluster, Refine: A Joint Embedding Predictive Self-Supervised Framework for Graph Representation Learning","created":"2025-02-02","cited_by_count":0,"area":null},{"id":"2512.15112","title":"Feature-Centric Unsupervised Node Representation Learning Without Homophily Assumption","created":"2025-12-17","cited_by_count":0,"area":null},{"id":"2602.05036","title":"Feedback Control for Multi-Objective Graph Self-Supervision","created":"2026-02-04","cited_by_count":0,"area":null},{"id":"2605.06576","title":"On the Safety of Graph Representation Learning","created":"2026-05-07","cited_by_count":0,"area":null},{"id":"2605.12685","title":"A Unified Perspective for Learning Graph Representations Across Multi-Level Abstractions","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2606.11898","title":"GraspLLM: Towards Zero-Shot Generalization on Text-Attributed Graphs with LLMs","created":"2026-06-10","cited_by_count":0,"area":null}],"next_cursor":null}