{"total":47,"rows":[{"id":"2404.16130","title":"From Local to Global: A Graph RAG Approach to Query-Focused Summarization","created":"2024-04-24","cited_by_count":1453,"area":"rag"},{"id":"2405.06211","title":"A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models","created":"2024-05-10","cited_by_count":452,"area":"rag"},{"id":"2402.19473","title":"Retrieval-Augmented Generation for AI-Generated Content: A Survey","created":"2024-02-29","cited_by_count":354,"area":"rag"},{"id":"2402.16893","title":"The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)","created":"2024-02-23","cited_by_count":159,"area":"rag"},{"id":"2405.13792","title":"xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token","created":"2024-05-22","cited_by_count":125,"area":"rag"},{"id":"2501.13958","title":"A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models","created":"2025-01-21","cited_by_count":88,"area":"rag"},{"id":"2404.10981","title":"A Survey on Retrieval-Augmented Text Generation for Large Language Models","created":"2024-04-17","cited_by_count":77,"area":"rag"},{"id":"2407.13193","title":"Retrieval-Augmented Generation for Natural Language Processing: A Survey","created":"2024-07-18","cited_by_count":71,"area":"rag"},{"id":"2409.14924","title":"Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely","created":"2024-09-23","cited_by_count":66,"area":"rag"},{"id":"2502.14902","title":"PathRAG: Pruning Graph-based Retrieval Augmented Generation with Relational Paths","created":"2025-02-18","cited_by_count":61,"area":"rag"},{"id":"2406.14773","title":"Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data","created":"2024-06-20","cited_by_count":52,"area":"rag"},{"id":"2401.17043","title":"CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Models","created":"2024-01-30","cited_by_count":50,"area":"rag"},{"id":"2403.01432","title":"Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledge","created":"2024-03-03","cited_by_count":50,"area":"rag"},{"id":"2405.16420","title":"M-RAG: Reinforcing Large Language Model Performance through Retrieval-Augmented Generation with Multiple Partitions","created":"2024-05-26","cited_by_count":38,"area":"rag"},{"id":"2507.18910","title":"A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions","created":"2025-07-25","cited_by_count":31,"area":"rag"},{"id":"2410.13339","title":"Probing-RAG: Self-Probing to Guide Language Models in Selective Document Retrieval","created":"2024-10-17","cited_by_count":29,"area":"rag"},{"id":"2506.00054","title":"Retrieval-Augmented Generation: A Comprehensive Survey of Architectures, Enhancements, and Robustness Frontiers","created":"2025-05-28","cited_by_count":27,"area":"rag"},{"id":"2504.11544","title":"NodeRAG: Structuring Graph-based RAG with Heterogeneous Nodes","created":"2025-04-15","cited_by_count":26,"area":"rag"},{"id":"2404.19543","title":"RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing","created":"2024-04-30","cited_by_count":25,"area":"rag"},{"id":"2501.14050","title":"GraphRAG under Fire","created":"2025-01-23","cited_by_count":24,"area":"rag"},{"id":"2411.01705","title":"Data Extraction Attacks in Retrieval-Augmented Generation via Backdoors","created":"2024-11-03","cited_by_count":23,"area":"rag"},{"id":"2406.07348","title":"DR-RAG: Applying Dynamic Document Relevance to Retrieval-Augmented Generation for Question-Answering","created":"2024-06-11","cited_by_count":14,"area":"rag"},{"id":"2403.14374","title":"FIT-RAG: Black-Box RAG with Factual Information and Token Reduction","created":"2024-03-21","cited_by_count":13,"area":"rag"},{"id":"2504.00573","title":"Training a Utility-based Retriever Through Shared Context Attribution for Retrieval-Augmented Language Models","created":"2025-04-01","cited_by_count":13,"area":"rag"},{"id":"2503.01346","title":"SRAG: Structured Retrieval-Augmented Generation for Multi-Entity Question Answering over Wikipedia Graph","created":"2025-03-03","cited_by_count":11,"area":"rag"},{"id":"2510.08935","title":"Personalize Before Retrieve: LLM-based Personalized Query Expansion for User-Centric Retrieval","created":"2025-10-10","cited_by_count":11,"area":"rag"},{"id":"2402.13542","title":"ARL2: Aligning Retrievers for Black-box Large Language Models via Self-guided Adaptive Relevance Labeling","created":"2024-02-21","cited_by_count":10,"area":"rag"},{"id":"2503.15548","title":"Privacy-Aware RAG: Secure and Isolated Knowledge Retrieval","created":"2025-03-17","cited_by_count":10,"area":"rag"},{"id":"2502.03233","title":"Exploring the Security Threats of Knowledge Base Poisoning in Retrieval-Augmented Code Generation","created":"2025-02-05","cited_by_count":9,"area":"rag"},{"id":"2505.22061","title":"Safeguarding Privacy of Retrieval Data against Membership Inference Attacks: Is This Query Too Close to Home?","created":"2025-05-28","cited_by_count":9,"area":"rag"},{"id":"2503.01713","title":"SAGE: A Framework of Precise Retrieval for RAG","created":"2025-03-03","cited_by_count":8,"area":"rag"},{"id":"2507.22931","title":"Enhancing RAG Efficiency with Adaptive Context Compression","created":"2025-07-24","cited_by_count":8,"area":"rag"},{"id":"2404.17897","title":"Tool Calling: Enhancing Medication Consultation via Retrieval-Augmented Large Language Models","created":"2024-04-27","cited_by_count":6,"area":"rag"},{"id":"2412.15272","title":"SimGRAG: Leveraging Similar Subgraphs for Knowledge Graphs Driven Retrieval-Augmented Generation","created":"2024-12-17","cited_by_count":6,"area":"rag"},{"id":"2402.04411","title":"DFA-RAG: Conversational Semantic Router for Large Language Model with Definite Finite Automaton","created":"2024-02-06","cited_by_count":5,"area":"rag"},{"id":"2409.00636","title":"A Learnable Agent Collaboration Network Framework for Personalized Multimodal AI Search Engine","created":"2024-09-01","cited_by_count":5,"area":"rag"},{"id":"2405.15198","title":"RAEE: A Robust Retrieval-Augmented Early Exit Framework for Efficient Inference","created":"2024-05-24","cited_by_count":4,"area":"rag"},{"id":"2406.03963","title":"A + B: A General Generator-Reader Framework for Optimizing LLMs to Unleash Synergy Potential","created":"2024-06-06","cited_by_count":3,"area":"rag"},{"id":"2511.05302","title":"When More Retrieval Hurts: Retrieval-Augmented Code Review Generation","created":"2025-11-07","cited_by_count":2,"area":"rag"},{"id":"2602.05235","title":"FedMosaic: Federated Retrieval-Augmented Generation via Parametric Adapters","created":"2026-02-05","cited_by_count":2,"area":"rag"},{"id":"2405.02659","title":"R4: Reinforced Retriever-Reorder-Responder for Retrieval-Augmented Large Language Models","created":"2024-05-04","cited_by_count":1,"area":"rag"},{"id":"2508.18929","title":"Diverse And Private Synthetic Datasets Generation for RAG evaluation: A multi-agent framework","created":"2025-08-26","cited_by_count":1,"area":"rag"},{"id":"2605.16113","title":"DebiasRAG: A Tuning-Free Path to Fair Generation in Large Language Models through Retrieval-Augmented Generation","created":"2026-05-15","cited_by_count":1,"area":"rag"},{"id":"2508.02296","title":"Knowing When Not to Answer: Lightweight KB-Aligned OOD Detection for Safe RAG","created":"2025-08-04","cited_by_count":0,"area":"rag"},{"id":"2601.16984","title":"TelcoAI: Advancing 3GPP Technical Specification Search through Agentic Multi-Modal Retrieval-Augmented Generation","created":"2025-11-17","cited_by_count":0,"area":"rag"},{"id":"2603.09347","title":"The Virtuous Cycle: AI-Powered Vector Search and Vector Search-Augmented AI","created":"2026-03-10","cited_by_count":0,"area":"rag"},{"id":"2609.05152","title":"Compression Beyond the Uncompressed: A Two-Stage Training Recipe for Soft Context Compression in RAG","created":"2026-09-04","cited_by_count":0,"area":"rag"}],"next_cursor":null}