{"total":29,"rows":[{"id":"2503.10677","title":"A Survey on Knowledge-Oriented Retrieval-Augmented Generation","created":"2025-03-11","cited_by_count":36,"area":"rag"},{"id":"2503.00353","title":"U-NIAH: Unified RAG and LLM Evaluation for Long Context Needle-In-A-Haystack","created":"2025-03-01","cited_by_count":20,"area":"rag"},{"id":"2412.12559","title":"EXIT: Context-Aware Extractive Compression for Enhancing Retrieval-Augmented Generation","created":"2024-12-17","cited_by_count":17,"area":"rag"},{"id":"2504.19754","title":"Reconstructing Context: Evaluating Advanced Chunking Strategies for Retrieval-Augmented Generation","created":"2025-04-28","cited_by_count":13,"area":"rag"},{"id":"2509.11552","title":"HiChunk: Evaluating and Enhancing Retrieval-Augmented Generation with Hierarchical Chunking","created":"2025-09-15","cited_by_count":12,"area":"rag"},{"id":"2510.06999","title":"Towards Reliable Retrieval in RAG Systems for Large Legal Datasets","created":"2025-10-08","cited_by_count":12,"area":"rag"},{"id":"2506.20821","title":"MultiFinRAG: An Optimized Multimodal Retrieval-Augmented Generation (RAG) Framework for Financial Question Answering","created":"2025-06-25","cited_by_count":9,"area":"rag"},{"id":"2504.10529","title":"HeteRAG: A Heterogeneous Retrieval-augmented Generation Framework with Decoupled Knowledge Representations","created":"2025-04-12","cited_by_count":6,"area":"rag"},{"id":"2509.17395","title":"FinDebate: Multi-Agent Collaborative Intelligence for Financial Analysis","created":"2025-09-22","cited_by_count":4,"area":"rag"},{"id":"2604.01733","title":"From BM25 to Corrective RAG: Benchmarking Retrieval Strategies for Text-and-Table Documents","created":"2026-04-02","cited_by_count":2,"area":"rag"},{"id":"2601.05265","title":"Cross-Document Topic-Aligned Chunking for Retrieval-Augmented Generation","created":"2025-11-08","cited_by_count":1,"area":"rag"},{"id":"2602.22225","title":"SmartChunk Retrieval: Query-Aware Chunk Compression with Planning for Efficient Document RAG","created":"2025-12-17","cited_by_count":1,"area":"rag"},{"id":"2603.07612","title":"KohakuRAG: A simple RAG framework with hierarchical document indexing","created":"2026-03-08","cited_by_count":1,"area":"rag"},{"id":"2603.22633","title":"Graph-Aware Late Chunking for Retrieval-Augmented Generation in Biomedical Literature","created":"2026-03-23","cited_by_count":1,"area":"rag"},{"id":"2603.25333","title":"Adaptive Chunking: Optimizing Chunking-Method Selection for RAG","created":"2026-03-26","cited_by_count":1,"area":"rag"},{"id":"2604.20849","title":"SPIRE: Structure-Preserving Interpretable Retrieval of Evidence","created":"2026-02-12","cited_by_count":1,"area":"rag"},{"id":"2604.24334","title":"Reducing Redundancy in Retrieval-Augmented Generation through Chunk Filtering","created":"2026-04-27","cited_by_count":1,"area":"rag"},{"id":"2606.00881","title":"Chunking Methods on Retrieval-Augmented Generation - Effectiveness Evaluation Against Computational Cost and Limitations","created":"2026-05-30","cited_by_count":1,"area":"rag"},{"id":"2607.01852","title":"Evaluating Chunking Strategies for Retrieval-Augmented Generation on Academic Texts","created":"2026-07-02","cited_by_count":1,"area":"rag"},{"id":"2510.13329","title":"Embedding-Based Context-Aware Reranker","created":"2025-10-15","cited_by_count":0,"area":"rag"},{"id":"2602.12278","title":"AttentionRetriever: Attention Layers are Secretly Long Document Retrievers","created":"2026-02-12","cited_by_count":0,"area":"rag"},{"id":"2603.18409","title":"TopoChunker: Topology-Aware Agentic Document Chunking Framework","created":"2026-03-19","cited_by_count":0,"area":"rag"},{"id":"2603.23533","title":"MDKeyChunker: Single-Call LLM Enrichment with Rolling Keys and Key-Based Restructuring for High-Accuracy RAG","created":"2026-03-08","cited_by_count":0,"area":"rag"},{"id":"2604.17677","title":"Semantic Entanglement in Vector-Based Retrieval: A Formal Framework and Context-Conditioned Disentanglement Pipeline for Agentic RAG Systems","created":"2026-04-20","cited_by_count":0,"area":"rag"},{"id":"2605.22203","title":"Evaluation of Chunking Strategies for Effective Text Embedding in Low-Resource Language on Agricultural Documents","created":"2026-05-21","cited_by_count":0,"area":"rag"},{"id":"2606.18381","title":"SproutRAG: Attention-Guided Tree Search with Progressive Embeddings for Long-Document RAG","created":"2026-06-16","cited_by_count":0,"area":"rag"},{"id":"2608.21610","title":"Semantic Compression Trees: Multi-Resolution Knowledge Retrieval via Hierarchical Semantic Residuals","created":"2026-08-21","cited_by_count":0,"area":"rag"},{"id":"2608.31139","title":"Configurable Semantic Chunking for Biomedical Information Extraction in Retrieval-Augmented Generation","created":"2026-08-31","cited_by_count":0,"area":"rag"},{"id":"2610.10170","title":"Does Document Structure Help Dense Retrieval? A Placebo-Controlled Ablation of Four Mechanisms Across Two Corpora","created":"2026-10-07","cited_by_count":0,"area":"rag"}],"next_cursor":null}