{"total":56,"rows":[{"id":"2501.00309","title":"Retrieval-Augmented Generation with Graphs (GraphRAG)","created":"2024-12-31","cited_by_count":172,"area":"rag"},{"id":"2410.03834","title":"GraphRouter: A Graph-based Router for LLM Selections","created":"2024-10-04","cited_by_count":165,"area":null},{"id":"2407.20060","title":"RelBench: A Benchmark for Deep Learning on Relational Databases","created":"2024-07-29","cited_by_count":96,"area":null},{"id":"2402.16785","title":"CARTE: Pretraining and Transfer for Tabular Learning","created":"2024-02-26","cited_by_count":76,"area":null},{"id":"2408.10700","title":"AnyGraph: Graph Foundation Model in the Wild","created":"2024-08-20","cited_by_count":53,"area":"moe"},{"id":"2502.06784","title":"RelGNN: Composite Message Passing for Relational Deep Learning","created":"2025-02-10","cited_by_count":48,"area":null},{"id":"2505.05568","title":"Griffin: Towards a Graph-Centric Relational Database Foundation Model","created":"2025-05-08","cited_by_count":47,"area":null},{"id":"2404.00776","title":"PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning","created":"2024-03-31","cited_by_count":32,"area":null},{"id":"2402.11139","title":"LiGNN: Graph Neural Networks at LinkedIn","created":"2024-02-17","cited_by_count":31,"area":null},{"id":"2504.12330","title":"HM-RAG: Hierarchical Multi-Agent Multimodal Retrieval Augmented Generation","created":"2025-04-13","cited_by_count":31,"area":"rag"},{"id":"2506.05725","title":"Large Language Models are Good Relational Learners","created":"2025-06-06","cited_by_count":24,"area":null},{"id":"2411.19513","title":"ContextGNN: Beyond Two-Tower Recommendation Systems","created":"2024-11-29","cited_by_count":19,"area":null},{"id":"2604.12596","title":"KumoRFM-2: Scaling Foundation Models for Relational Learning","created":"2026-04-14","cited_by_count":19,"area":null},{"id":"2504.01346","title":"RAG over Tables: Hierarchical Memory Index, Multi-Stage Retrieval, and Benchmarking","created":"2025-04-02","cited_by_count":18,"area":"rag"},{"id":"2507.10539","title":"Graph World Model","created":"2025-07-14","cited_by_count":16,"area":"wm"},{"id":"2411.11829","title":"Tackling prediction tasks in relational databases with LLMs","created":"2024-11-18","cited_by_count":14,"area":null},{"id":"2603.03805","title":"Relational In-Context Learning via Synthetic Pre-training with Structural Prior","created":"2026-03-04","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":"2403.07478","title":"Towards Graph Foundation Models for Personalization","created":"2024-03-12","cited_by_count":12,"area":null},{"id":"2404.18209","title":"4DBInfer: A 4D Benchmarking Toolbox for Graph-Centric Predictive Modeling on Relational DBs","created":"2024-04-28","cited_by_count":11,"area":null},{"id":"2602.13697","title":"No Need to Train Your RDB Foundation Model","created":"2026-02-14","cited_by_count":10,"area":null},{"id":"2505.16527","title":"Joint Relational Database Generation via Graph-Conditional Diffusion Models","created":"2025-05-22","cited_by_count":9,"area":"diffusion"},{"id":"2412.17029","title":"GraphAgent: Agentic Graph Language Assistant","created":"2024-12-22","cited_by_count":8,"area":"agents"},{"id":"2506.01360","title":"RDB2G-Bench: A Comprehensive Benchmark for Automatic Graph Modeling of Relational Databases","created":"2025-06-02","cited_by_count":8,"area":null},{"id":"2509.10697","title":"A Survey on Retrieval And Structuring Augmented Generation with Large Language Models","created":"2025-09-12","cited_by_count":8,"area":null},{"id":"2407.20157","title":"rLLM: Relational Table Learning with LLMs","created":"2024-07-29","cited_by_count":7,"area":null},{"id":"2410.03411","title":"Benchmarking the Fidelity and Utility of Synthetic Relational Data","created":"2024-10-04","cited_by_count":7,"area":null},{"id":"2412.00521","title":"A Self-Explainable Heterogeneous GNN for Relational Deep Learning","created":"2024-11-30","cited_by_count":7,"area":null},{"id":"2402.06282","title":"Retrieve, Merge, Predict: Augmenting Tables with Data Lakes","created":"2024-02-09","cited_by_count":5,"area":null},{"id":"2406.16013","title":"Database-Augmented Query Representation for Information Retrieval","created":"2024-06-23","cited_by_count":5,"area":null},{"id":"2602.18495","title":"RDBLearn: Simple In-Context Prediction Over Relational Databases","created":"2026-02-14","cited_by_count":5,"area":null},{"id":"2606.18621","title":"Towards Anomaly Detection on Relational Data","created":"2026-06-17","cited_by_count":5,"area":null},{"id":"2511.04557","title":"Integrating Temporal and Structural Context in Graph Transformers for Relational Deep Learning","created":"2025-11-06","cited_by_count":4,"area":null},{"id":"2511.16883","title":"PersonalizedRouter: Personalized LLM Routing via Graph-based User Preference Modeling","created":"2025-11-21","cited_by_count":4,"area":null},{"id":"2606.24509","title":"A Fair Evaluation of Graph Foundation Models for Node Property Prediction","created":"2026-06-23","cited_by_count":4,"area":null},{"id":"2406.00578","title":"ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-Variable Context Encoding","created":"2024-06-02","cited_by_count":3,"area":null},{"id":"2511.08846","title":"On topological descriptors for graph products","created":"2025-11-12","cited_by_count":3,"area":null},{"id":"2606.06397","title":"The Post-GCN Decade Revisited: Curvature-Stratified Evaluation of Relational Learning","created":"2026-06-04","cited_by_count":3,"area":null},{"id":"2405.18670","title":"Differentially Private Synthetic Data Generation for Relational Databases","created":"2024-05-29","cited_by_count":2,"area":null},{"id":"2506.06582","title":"Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing","created":"2025-06-06","cited_by_count":2,"area":null},{"id":"2507.10281","title":"Toward Real-World Table Agents: Capabilities, Workflows, and Design Principles for LLM-based Table Intelligence","created":"2025-07-14","cited_by_count":2,"area":"agents"},{"id":"2602.07126","title":"Finding Connections: Membership Inference Attacks for the Multi-Table Synthetic Data Setting","created":"2026-02-06","cited_by_count":2,"area":"safety"},{"id":"2603.29914","title":"Task Scarcity and Label Leakage in Relational Transfer Learning","created":"2026-03-31","cited_by_count":2,"area":null},{"id":"2406.11249","title":"Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective","created":"2024-06-17","cited_by_count":1,"area":null},{"id":"2411.11375","title":"Graph Neural Networks on Graph Databases","created":"2024-11-18","cited_by_count":1,"area":null},{"id":"2607.03659","title":"A Fair Benchmarking of Deep Relational Database Learning Models","created":"2026-07-04","cited_by_count":1,"area":null},{"id":"2508.20986","title":"Graph-Based Feature Augmentation for Predictive Tasks on Relational Datasets","created":"2025-08-28","cited_by_count":0,"area":null},{"id":"2510.04543","title":"The Role of Feature Interactions in Graph-based Tabular Deep Learning","created":"2025-10-06","cited_by_count":0,"area":null},{"id":"2602.01553","title":"Plain Transformers are Surprisingly Powerful Link Predictors","created":"2026-02-02","cited_by_count":0,"area":null},{"id":"2606.27863","title":"GNBAN: Graph Neural Basis Attention Networks for Long-Horizon Forecasting over Large Entity Sets","created":"2026-06-26","cited_by_count":0,"area":null},{"id":"2607.05478","title":"InvWeaver: Deductive Feedback for Invariant Synthesis in Interacting-Loop Programs","created":"2026-07-06","cited_by_count":0,"area":null},{"id":"2607.14102","title":"UniSAGE: Unifying Static and Dynamic Attributes with Hyper-Structure","created":"2026-05-06","cited_by_count":0,"area":null},{"id":"2609.00457","title":"Can LLMs Use Relational Transformer Embeddings?","created":"2026-08-31","cited_by_count":0,"area":"lr"},{"id":"2609.05748","title":"A Multi-Source Ensemble Approach to Candidate Generation for Alternative Vacation Rental Property Recommendations","created":"2026-09-04","cited_by_count":0,"area":null},{"id":"2609.11347","title":"Reification as a Transferable Vocabulary: Zero-Shot Link Prediction with Vanilla GNNs","created":"2026-09-10","cited_by_count":0,"area":null},{"id":"2610.20534","title":"Revisiting Simple Baselines for Relational Deep Learning","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}