{"total":144,"rows":[{"id":"2307.02046","title":"Recommender Systems in the Era of Large Language Models (LLMs)","created":"2023-07-05","cited_by_count":189,"area":null},{"id":"2205.07424","title":"Trustworthy Graph Neural Networks: Aspects, Methods and Trends","created":"2022-05-16","cited_by_count":89,"area":null},{"id":"2212.04481","title":"A Survey of Graph Neural Networks for Social Recommender Systems","created":"2022-12-08","cited_by_count":65,"area":null},{"id":"2211.08854","title":"Graph Filters for Signal Processing and Machine Learning on Graphs","created":"2022-11-16","cited_by_count":53,"area":null},{"id":"2503.05659","title":"A Survey of Large Language Model Empowered Agents for Recommendation and Search: Towards Next-Generation Information Retrieval","created":"2025-03-07","cited_by_count":33,"area":"agents"},{"id":"2403.02990","title":"Data Augmentation using Large Language Models: Data Perspectives, Learning Paradigms and Challenges","created":"2024-03-05","cited_by_count":30,"area":null},{"id":"2212.12488","title":"Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection","created":"2022-12-23","cited_by_count":26,"area":null},{"id":"2505.19623","title":"AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems","created":"2025-05-26","cited_by_count":23,"area":"lr"},{"id":"2310.02152","title":"Graph Neural Network-based EEG Classification: A Survey","created":"2023-10-03","cited_by_count":21,"area":null},{"id":"2302.00058","title":"Graph Anomaly Detection in Time Series: A Survey","created":"2023-01-31","cited_by_count":18,"area":null},{"id":"2311.16716","title":"GraphPro: Graph Pre-training and Prompt Learning for Recommendation","created":"2023-11-28","cited_by_count":17,"area":null},{"id":"2405.14407","title":"Dynamic Graph Unlearning: A General and Efficient Post-Processing Method via Gradient Transformation","created":"2024-05-23","cited_by_count":15,"area":"safety"},{"id":"2205.15765","title":"Strategic Classification with Graph Neural Networks","created":"2022-05-31","cited_by_count":14,"area":null},{"id":"2407.11060","title":"A review of graph neural network applications in mechanics-related domains","created":"2024-07-10","cited_by_count":14,"area":null},{"id":"2401.02143","title":"Graph Neural Networks for Tabular Data Learning: A Survey with Taxonomy and Directions","created":"2024-01-04","cited_by_count":13,"area":null},{"id":"2402.06330","title":"Continual Learning on Graphs: A Survey","created":"2024-02-09","cited_by_count":12,"area":null},{"id":"2307.08924","title":"Towards Task Sampler Learning for Meta-Learning","created":"2023-07-18","cited_by_count":11,"area":null},{"id":"2408.08821","title":"EasyRec: Simple yet Effective Language Models for Recommendation","created":"2024-08-16","cited_by_count":10,"area":null},{"id":"2412.18241","title":"An Automatic Graph Construction Framework based on Large Language Models for Recommendation","created":"2024-12-24","cited_by_count":9,"area":null},{"id":"2305.18758","title":"Task-Equivariant Graph Few-shot Learning","created":"2023-05-30","cited_by_count":8,"area":null},{"id":"2402.15326","title":"Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory","created":"2024-02-23","cited_by_count":8,"area":null},{"id":"2410.17555","title":"FairDgcl: Fairness-aware Recommendation with Dynamic Graph Contrastive Learning","created":"2024-10-23","cited_by_count":8,"area":null},{"id":"2510.05036","title":"Graph-Aware Diffusion for Signal Generation","created":"2025-10-06","cited_by_count":8,"area":null},{"id":"2304.09097","title":"Sheaf4Rec: Sheaf Neural Networks for Graph-based Recommender Systems","created":"2023-04-07","cited_by_count":7,"area":null},{"id":"2402.03365","title":"Heterophily-Aware Fair Recommendation using Graph Convolutional Networks","created":"2024-01-31","cited_by_count":7,"area":null},{"id":"2408.02691","title":"Symmetric Graph Contrastive Learning against Noisy Views for Recommendation","created":"2024-08-03","cited_by_count":7,"area":null},{"id":"2501.15555","title":"Distributionally Robust Graph Out-of-Distribution Recommendation via Diffusion Model","created":"2025-01-26","cited_by_count":7,"area":"diffusion"},{"id":"2505.09777","title":"A Survey on Large Language Models in Multimodal Recommender Systems","created":"2025-05-14","cited_by_count":7,"area":null},{"id":"2210.00538","title":"Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation","created":"2022-10-02","cited_by_count":6,"area":null},{"id":"2406.06984","title":"On the H\\\"{o}lder Stability of Multiset and Graph Neural Networks","created":"2024-06-11","cited_by_count":6,"area":null},{"id":"2408.06524","title":"From Graphs to Qubits: A Critical Review of Quantum Graph Neural Networks","created":"2024-08-12","cited_by_count":6,"area":null},{"id":"2412.13544","title":"Bridging the User-side Knowledge Gap in Knowledge-aware Recommendations with Large Language Models","created":"2024-12-18","cited_by_count":6,"area":null},{"id":"2307.09866","title":"Detecting Vulnerable Nodes in Urban Infrastructure Interdependent Network","created":"2023-07-19","cited_by_count":5,"area":null},{"id":"2403.11624","title":"Dual-Channel Multiplex Graph Neural Networks for Recommendation","created":"2024-03-18","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":"2508.11977","title":"TBGRecall: A Generative Retrieval Model for E-commerce Recommendation Scenarios","created":"2025-08-16","cited_by_count":5,"area":null},{"id":"2307.11234","title":"QDC: Quantum Diffusion Convolution Kernels on Graphs","created":"2023-07-20","cited_by_count":4,"area":null},{"id":"2401.09071","title":"Rethinking Spectral Graph Neural Networks with Spatially Adaptive Filtering","created":"2024-01-17","cited_by_count":4,"area":null},{"id":"2403.07916","title":"Advancing Investment Frontiers: Industry-grade Deep Reinforcement Learning for Portfolio Optimization","created":"2024-02-27","cited_by_count":4,"area":"deeprl"},{"id":"2403.16656","title":"Graph Augmentation for Recommendation","created":"2024-03-25","cited_by_count":4,"area":null},{"id":"2405.12327","title":"Beyond Item Dissimilarities: Diversifying by Intent in Recommender Systems","created":"2024-05-20","cited_by_count":4,"area":null},{"id":"2405.17309","title":"Survey of Graph Neural Network for Internet of Things and NextG Networks","created":"2024-05-27","cited_by_count":4,"area":null},{"id":"2502.08346","title":"Graph Foundation Models for Recommendation: A Comprehensive Survey","created":"2025-02-12","cited_by_count":4,"area":null},{"id":"2505.20807","title":"Simple yet Effective Graph Distillation via Clustering","created":"2025-05-27","cited_by_count":4,"area":null},{"id":"2507.07405","title":"HGMP:Heterogeneous Graph Multi-Task Prompt Learning","created":"2025-07-10","cited_by_count":4,"area":null},{"id":"2602.00682","title":"RecGOAT: Graph Optimal Adaptive Transport for LLM-Enhanced Multimodal Recommendation with Dual Semantic Alignment","created":"2026-01-31","cited_by_count":4,"area":null},{"id":"2307.11004","title":"Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering","created":"2023-07-12","cited_by_count":3,"area":null},{"id":"2307.13206","title":"Transferability of Graph Neural Networks using Graphon and Sampling Theories","created":"2023-07-25","cited_by_count":3,"area":null},{"id":"2310.19394","title":"LightSAGE: Graph Neural Networks for Large Scale Item Retrieval in Shopee's Advertisement Recommendation","created":"2023-10-30","cited_by_count":3,"area":null},{"id":"2401.01384","title":"Strong Transitivity Relations and Graph Neural Networks","created":"2024-01-01","cited_by_count":3,"area":null},{"id":"2411.03663","title":"Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach","created":"2024-11-06","cited_by_count":3,"area":null},{"id":"2501.10548","title":"Diffusion Models in Recommendation Systems: A Survey","created":"2025-01-17","cited_by_count":3,"area":"diffusion"},{"id":"2505.23345","title":"Graph Positional Autoencoders as Self-supervised Learners","created":"2025-05-29","cited_by_count":3,"area":null},{"id":"2507.16829","title":"You Don't Bring Me Flowers: Mitigating Unwanted Recommendations Through Conformal Risk Control","created":"2025-07-09","cited_by_count":3,"area":null},{"id":"2508.00201","title":"RecoMind: A Reinforcement Learning Framework for Optimizing In-Session User Satisfaction in Recommendation Systems","created":"2025-07-31","cited_by_count":3,"area":"deeprl"},{"id":"2602.07708","title":"Quantifying Explanation Quality in Graph Neural Networks using Out-of-Distribution Generalization","created":"2026-02-07","cited_by_count":3,"area":null},{"id":"2303.02204","title":"KGLiDS: A Platform for Semantic Abstraction, Linking, and Automation of Data Science","created":"2023-03-03","cited_by_count":2,"area":null},{"id":"2308.14601","title":"Fairness Through Domain Awareness: Mitigating Popularity Bias For Music Discovery","created":"2023-08-28","cited_by_count":2,"area":null},{"id":"2311.12255","title":"Exploring Time Granularity on Temporal Graphs for Dynamic Link Prediction in Real-world Networks","created":"2023-11-21","cited_by_count":2,"area":null},{"id":"2312.08672","title":"CAT: A Causally Graph Attention Network for Trimming Heterophilic Graph","created":"2023-12-14","cited_by_count":2,"area":null},{"id":"2406.06658","title":"Link Prediction in Bipartite Networks","created":"2024-06-10","cited_by_count":2,"area":null},{"id":"2408.15371","title":"Temporal Graph Neural Network-Powered Paper Recommendation on Dynamic Citation Networks","created":"2024-08-27","cited_by_count":2,"area":null},{"id":"2409.09079","title":"D3-GNN: Dynamic Distributed Dataflow for Streaming Graph Neural Networks","created":"2024-09-10","cited_by_count":2,"area":null},{"id":"2412.08066","title":"Cluster-Enhanced Federated Graph Neural Network for Recommendation","created":"2024-12-11","cited_by_count":2,"area":null},{"id":"2505.08157","title":"Hyperbolic Contrastive Learning with Model-augmentation for Knowledge-aware Recommendation","created":"2025-05-13","cited_by_count":2,"area":null},{"id":"2505.11318","title":"On the Role of Weight Decay in Collaborative Filtering: A Popularity Perspective","created":"2025-05-16","cited_by_count":2,"area":null},{"id":"2506.13777","title":"A Survey of Physics-Informed AI for Complex Urban Systems","created":"2025-06-09","cited_by_count":2,"area":null},{"id":"2509.01549","title":"Ultra Fast Warm Start Solution for Graph Recommendations","created":"2025-09-01","cited_by_count":2,"area":null},{"id":"2510.07716","title":"Computationally-efficient Graph Modeling with Refined Graph Random Features","created":"2025-10-09","cited_by_count":2,"area":null},{"id":"2112.10085","title":"D-HAN: Dynamic News Recommendation with Hierarchical Attention Network","created":"2021-12-19","cited_by_count":1,"area":null},{"id":"2308.09259","title":"FRGNN: Mitigating the Impact of Distribution Shift on Graph Neural Networks via Test-Time Feature Reconstruction","created":"2023-08-18","cited_by_count":1,"area":null},{"id":"2310.00431","title":"ResolvNet: A Graph Convolutional Network with multi-scale Consistency","created":"2023-09-30","cited_by_count":1,"area":null},{"id":"2310.15858","title":"Topology-aware Debiased Self-supervised Graph Learning for Recommendation","created":"2023-10-24","cited_by_count":1,"area":null},{"id":"2311.06777","title":"Alleviating Behavior Data Imbalance for Multi-Behavior Graph Collaborative Filtering","created":"2023-11-12","cited_by_count":1,"area":null},{"id":"2311.07632","title":"ResMGCN: Residual Message Graph Convolution Network for Fast Biomedical Interactions Discovering","created":"2023-11-13","cited_by_count":1,"area":null},{"id":"2312.16542","title":"FALCON: Feature-Label Constrained Graph Net Collapse for Memory Efficient GNNs","created":"2023-12-27","cited_by_count":1,"area":null},{"id":"2403.00895","title":"End-to-End Graph-Sequential Representation Learning for Accurate Recommendations","created":"2024-03-01","cited_by_count":1,"area":null},{"id":"2405.11968","title":"Conditional Shift-Robust Conformal Prediction for Graph Neural Network","created":"2024-05-20","cited_by_count":1,"area":null},{"id":"2406.04553","title":"Better Late Than Never: Formulating and Benchmarking Recommendation Editing","created":"2024-06-06","cited_by_count":1,"area":null},{"id":"2407.21191","title":"GenRec: Generative Sequential Recommendation with Large Language Models","created":"2024-07-30","cited_by_count":1,"area":null},{"id":"2408.00166","title":"Review of Explainable Graph-Based Recommender Systems","created":"2024-07-31","cited_by_count":1,"area":null},{"id":"2408.12208","title":"Fair Augmentation for Graph Collaborative Filtering","created":"2024-08-22","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":"2409.06998","title":"Mixture of Scope Experts at Test: Generalizing Deeper Graph Neural Networks with Shallow Variants","created":"2024-09-11","cited_by_count":1,"area":null},{"id":"2409.08474","title":"Rethinking Meta-Learning from a Learning Lens","created":"2024-09-13","cited_by_count":1,"area":null},{"id":"2410.12086","title":"Comparative Performance of Collaborative Bandit Algorithms: Effect of Sparsity and Exploration Intensity","created":"2024-10-15","cited_by_count":1,"area":null},{"id":"2410.13373","title":"Addressing Graph Heterogeneity and Heterophily from A Spectral Perspective","created":"2024-10-17","cited_by_count":1,"area":null},{"id":"2410.23300","title":"Understanding and Scaling Collaborative Filtering Optimization from the Perspective of Matrix Rank","created":"2024-10-15","cited_by_count":1,"area":null},{"id":"2504.13614","title":"Adaptive Long-term Embedding with Denoising and Augmentation for Recommendation","created":"2025-04-18","cited_by_count":1,"area":null},{"id":"2506.02752","title":"BenLOC: A Benchmark for Learning to Configure MIP Optimizers","created":"2025-06-03","cited_by_count":1,"area":null},{"id":"2506.08743","title":"Bridging RDF Knowledge Graphs with Graph Neural Networks for Semantically-Rich Recommender Systems","created":"2025-06-10","cited_by_count":1,"area":null},{"id":"2506.21368","title":"Real-time and personalized product recommendations for large e-commerce platforms","created":"2025-06-26","cited_by_count":1,"area":null},{"id":"2506.22648","title":"Interact2Vec -- An efficient neural network-based model for simultaneously learning users and items embeddings in recommender systems","created":"2025-06-27","cited_by_count":1,"area":null},{"id":"2507.14352","title":"A Reproducibility Study of Product-side Fairness in Bundle Recommendation","created":"2025-07-18","cited_by_count":1,"area":null},{"id":"2510.11903","title":"Integrating Sequential and Relational Modeling for User Events: Datasets and Prediction Tasks","created":"2025-10-13","cited_by_count":1,"area":null},{"id":"2510.27274","title":"Traceable Drug Recommendation over Medical Knowledge Graphs","created":"2025-10-31","cited_by_count":1,"area":null},{"id":"2601.08033","title":"InfGraND: An Influence-Guided GNN-to-MLP Knowledge Distillation","created":"2026-01-12","cited_by_count":1,"area":"distill"},{"id":"2603.02938","title":"Beyond One-Size-Fits-All: Adaptive Subgraph Denoising for Zero-Shot Graph Learning with Large Language Models","created":"2026-03-03","cited_by_count":1,"area":null},{"id":"2607.28980","title":"Beyond Feature and Structure Alignment: Learning Transferable Propagation Knowledge for Graph Foundation Models","created":"2026-07-31","cited_by_count":1,"area":null},{"id":"2111.07154","title":"Session-aware Item-combination Recommendation with Transformer Network","created":"2021-11-13","cited_by_count":0,"area":null}],"next_cursor":"100"}