{"total":21,"rows":[{"id":"2301.12652","title":"REPLUG: Retrieval-Augmented Black-Box Language Models","created":"2023-01-30","cited_by_count":792,"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":"2403.03187","title":"Reliable, Adaptable, and Attributable Language Models with Retrieval","created":"2024-03-05","cited_by_count":73,"area":"rag"},{"id":"2310.15205","title":"DISC-FinLLM: A Chinese Financial Large Language Model based on Multiple Experts Fine-tuning","created":"2023-10-23","cited_by_count":64,"area":"rag"},{"id":"2403.10081","title":"DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language Models","created":"2024-03-15","cited_by_count":63,"area":"rag"},{"id":"2310.18347","title":"PRCA: Fitting Black-Box Large Language Models for Retrieval Question Answering via Pluggable Reward-Driven Contextual Adapter","created":"2023-10-23","cited_by_count":38,"area":"rag"},{"id":"2501.15915","title":"Parametric Retrieval Augmented Generation","created":"2025-01-27","cited_by_count":38,"area":"rag"},{"id":"2310.15556","title":"TCRA-LLM: Token Compression Retrieval Augmented Large Language Model for Inference Cost Reduction","created":"2023-10-24","cited_by_count":34,"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":"2503.14258","title":"JuDGE: Benchmarking Judgment Document Generation for Chinese Legal System","created":"2025-03-18","cited_by_count":18,"area":"rag"},{"id":"2405.03085","title":"Compressing Long Context for Enhancing RAG with AMR-based Concept Distillation","created":"2024-05-06","cited_by_count":16,"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":"2307.12798","title":"RRAML: Reinforced Retrieval Augmented Machine Learning","created":"2023-07-24","cited_by_count":6,"area":"rag"},{"id":"2408.05524","title":"Context-Driven Index Trimming: A Data Quality Perspective to Enhancing Precision of RALMs","created":"2024-08-10","cited_by_count":5,"area":"rag"},{"id":"2409.06595","title":"GroUSE: A Benchmark to Evaluate Evaluators in Grounded Question Answering","created":"2024-09-10","cited_by_count":5,"area":"rag"},{"id":"2411.00451","title":"Improving Few-Shot Cross-Domain Named Entity Recognition by Instruction Tuning a Word-Embedding based Retrieval Augmented Large Language Model","created":"2024-11-01","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":"2404.02022","title":"Improving Retrieval Augmented Open-Domain Question-Answering with Vectorized Contexts","created":"2024-04-02","cited_by_count":3,"area":"rag"},{"id":"2504.08744","title":"ExpertRAG: Efficient RAG with Mixture of Experts -- Optimizing Context Retrieval for Adaptive LLM Responses","created":"2025-03-23","cited_by_count":2,"area":"rag"},{"id":"2312.02532","title":"DRAFT: Dense Retrieval Augmented Few-shot Topic classifier Framework","created":"2023-12-05","cited_by_count":1,"area":"rag"},{"id":"2603.23989","title":"CoCR-RAG: Enhancing Retrieval-Augmented Generation in Web Q&A via Concept-oriented Context Reconstruction","created":"2026-03-25","cited_by_count":0,"area":"rag"}],"next_cursor":null}