{"total":34,"rows":[{"id":"2402.19473","title":"Retrieval-Augmented Generation for AI-Generated Content: A Survey","created":"2024-02-29","cited_by_count":354,"area":"rag"},{"id":"2410.05779","title":"LightRAG: Simple and Fast Retrieval-Augmented Generation","created":"2024-10-08","cited_by_count":315,"area":"rag"},{"id":"2405.07437","title":"Evaluation of Retrieval-Augmented Generation: A Survey","created":"2024-05-13","cited_by_count":146,"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":"2408.08067","title":"RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation","created":"2024-08-15","cited_by_count":61,"area":"rag"},{"id":"2407.21059","title":"Modular RAG: Transforming RAG Systems into LEGO-like Reconfigurable Frameworks","created":"2024-07-26","cited_by_count":42,"area":"rag"},{"id":"2406.15187","title":"UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-world Document Analysis","created":"2024-06-21","cited_by_count":40,"area":"rag"},{"id":"2502.09977","title":"LaRA: Benchmarking Retrieval-Augmented Generation and Long-Context LLMs -- No Silver Bullet for LC or RAG Routing","created":"2025-02-14","cited_by_count":29,"area":"rag"},{"id":"2504.14891","title":"Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive Survey","created":"2025-04-21","cited_by_count":20,"area":"rag"},{"id":"2504.10499","title":"Graph-based Approaches and Functionalities in Retrieval-Augmented Generation: A Comprehensive Survey","created":"2025-04-08","cited_by_count":18,"area":"rag"},{"id":"2410.12788","title":"Meta-Chunking: Learning Text Segmentation and Semantic Completion via Logical Perception","created":"2024-10-16","cited_by_count":17,"area":"rag"},{"id":"2505.19864","title":"CPA-RAG:Covert Poisoning Attacks on Retrieval-Augmented Generation in Large Language Models","created":"2025-05-26","cited_by_count":17,"area":"rag"},{"id":"2505.15872","title":"InfoDeepSeek: Benchmarking Agentic Information Seeking for Retrieval-Augmented Generation","created":"2025-05-21","cited_by_count":15,"area":"rag"},{"id":"2405.16933","title":"Empowering Large Language Models to Set up a Knowledge Retrieval Indexer via Self-Learning","created":"2024-05-27","cited_by_count":13,"area":"rag"},{"id":"2412.05547","title":"KG-Retriever: Efficient Knowledge Indexing for Retrieval-Augmented Large Language Models","created":"2024-12-07","cited_by_count":12,"area":"rag"},{"id":"2409.13694","title":"Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study","created":"2024-09-03","cited_by_count":8,"area":"rag"},{"id":"2504.02458","title":"Retrieval-Augmented Purifier for Robust LLM-Empowered Recommendation","created":"2025-04-03","cited_by_count":7,"area":"rag"},{"id":"2504.20119","title":"Can LLMs Be Trusted for Evaluating RAG Systems? A Survey of Methods and Datasets","created":"2025-04-28","cited_by_count":7,"area":"rag"},{"id":"2602.00296","title":"RAGRouter-Bench: A Dataset and Benchmark for Adaptive RAG Routing","created":"2026-01-30","cited_by_count":6,"area":"rag"},{"id":"2509.01476","title":"Do Retrieval Augmented Language Models Know When They Don't Know?","created":"2025-09-01","cited_by_count":5,"area":"rag"},{"id":"2501.08208","title":"ASTRID -- An Automated and Scalable TRIaD for the Evaluation of RAG-based Clinical Question Answering Systems","created":"2025-01-14","cited_by_count":4,"area":"rag"},{"id":"2402.12177","title":"Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuning","created":"2024-02-19","cited_by_count":2,"area":"rag"},{"id":"2501.04858","title":"Advancing Retrieval-Augmented Generation for Persian: Development of Language Models, Comprehensive Benchmarks, and Best Practices for Optimization","created":"2025-01-08","cited_by_count":2,"area":"rag"},{"id":"2506.06331","title":"How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG","created":"2025-05-31","cited_by_count":2,"area":"rag"},{"id":"2603.11772","title":"Legal-DC: Benchmarking Retrieval-Augmented Generation for Legal Documents","created":"2026-03-12","cited_by_count":2,"area":"rag"},{"id":"2604.20763","title":"Coverage, Not Averages: Semantic Stratification for Trustworthy Retrieval Evaluation","created":"2026-04-22","cited_by_count":2,"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":"2411.02832","title":"PersianRAG: A Retrieval-Augmented Generation System for Persian Language","created":"2024-11-05","cited_by_count":0,"area":"rag"},{"id":"2510.20356","title":"FreeChunker: A Cross-Granularity Chunking Framework","created":"2025-10-23","cited_by_count":0,"area":"rag"},{"id":"2604.15270","title":"Enhancing Large Language Models with Retrieval Augmented Generation for Software Testing and Inspection Automation","created":"2026-04-16","cited_by_count":0,"area":"rag"},{"id":"2605.00957","title":"\"I Don't Know\" -- Towards Appropriate Trust with Certainty-Aware Retrieval Augmented Generation","created":"2026-05-01","cited_by_count":0,"area":"rag"},{"id":"2605.22829","title":"LFRAG: Layout-oriented Fine-grained Retrieval-Augmented Generation on Multimodal Document Understanding","created":"2026-04-18","cited_by_count":0,"area":"rag"},{"id":"2606.15482","title":"Ricci-Filtration: Boosting Retrieval-Augmented Generation Reranker to Query-Answer Tasks by Discrete Ricci Flow","created":"2026-06-13","cited_by_count":0,"area":"rag"},{"id":"2608.00054","title":"RAG-TESTER: Automated End-to-End Testing of Retrieval-Augmented Large Language Models","created":"2026-07-26","cited_by_count":0,"area":"rag"}],"next_cursor":null}