{"total":22,"rows":[{"id":"2208.03299","title":"Atlas: Few-shot Learning with Retrieval Augmented Language Models","created":"2022-08-05","cited_by_count":952,"area":"rag"},{"id":"2310.01352","title":"RA-DIT: Retrieval-Augmented Dual Instruction Tuning","created":"2023-10-02","cited_by_count":195,"area":"rag"},{"id":"2209.14290","title":"FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation","created":"2022-09-28","cited_by_count":63,"area":"rag"},{"id":"2405.03279","title":"Lifelong Knowledge Editing for LLMs with Retrieval-Augmented Continuous Prompt Learning","created":"2024-05-06","cited_by_count":40,"area":"rag"},{"id":"2503.10677","title":"A Survey on Knowledge-Oriented Retrieval-Augmented Generation","created":"2025-03-11","cited_by_count":36,"area":"rag"},{"id":"2405.02816","title":"Stochastic RAG: End-to-End Retrieval-Augmented Generation through Expected Utility Maximization","created":"2024-05-05","cited_by_count":29,"area":"rag"},{"id":"2108.13934","title":"Robust Retrieval Augmented Generation for Zero-shot Slot Filling","created":"2021-08-31","cited_by_count":24,"area":"rag"},{"id":"2405.00175","title":"Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language Models","created":"2024-04-30","cited_by_count":23,"area":"rag"},{"id":"2402.18150","title":"Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented Generation","created":"2024-02-28","cited_by_count":19,"area":"rag"},{"id":"2410.09942","title":"Learning to Rank for Multiple Retrieval-Augmented Models through Iterative Utility Maximization","created":"2024-10-13","cited_by_count":14,"area":"rag"},{"id":"2312.13040","title":"Retrieval-augmented Multilingual Knowledge Editing","created":"2023-12-20","cited_by_count":13,"area":"rag"},{"id":"2502.02464","title":"Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation","created":"2025-02-04","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":"2207.03030","title":"Multi-Task Retrieval-Augmented Text Generation with Relevance Sampling","created":"2022-07-07","cited_by_count":10,"area":"rag"},{"id":"2506.02279","title":"ImpRAG: Retrieval-Augmented Generation with Implicit Queries","created":"2025-06-02","cited_by_count":5,"area":"rag"},{"id":"2406.08116","title":"Supportiveness-based Knowledge Rewriting for Retrieval-augmented Language Modeling","created":"2024-06-12","cited_by_count":4,"area":"rag"},{"id":"2502.10596","title":"Post-training an LLM for RAG? Train on Self-Generated Demonstrations","created":"2025-02-14","cited_by_count":1,"area":"rag"},{"id":"2510.12668","title":"Understanding Parametric Knowledge Injection in Retrieval-Augmented Generation","created":"2025-10-14","cited_by_count":1,"area":"rag"},{"id":"2505.04844","title":"Osiris: A Lightweight Open-Source Hallucination Detection System","created":"2025-05-07","cited_by_count":0,"area":"rag"},{"id":"2506.02503","title":"KARE-RAG: Knowledge-Aware Refinement and Enhancement for RAG","created":"2025-06-03","cited_by_count":0,"area":"rag"},{"id":"2603.25737","title":"Training the Knowledge Base through Evidence Distillation and Write-Back Enrichment","created":"2026-03-26","cited_by_count":0,"area":"rag"},{"id":"2604.26768","title":"Decoupling Knowledge and Task Subspaces for Composable Parametric Retrieval Augmented Generation","created":"2026-04-29","cited_by_count":0,"area":"rag"}],"next_cursor":null}