{"total":25,"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":"2401.14887","title":"The Power of Noise: Redefining Retrieval for RAG Systems","created":"2024-01-26","cited_by_count":281,"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":"2403.01432","title":"Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledge","created":"2024-03-03","cited_by_count":50,"area":"rag"},{"id":"2401.07883","title":"The Chronicles of RAG: The Retriever, the Chunk and the Generator","created":"2024-01-15","cited_by_count":34,"area":"rag"},{"id":"2210.13693","title":"XRICL: Cross-lingual Retrieval-Augmented In-Context Learning for Cross-lingual Text-to-SQL Semantic Parsing","created":"2022-10-25","cited_by_count":33,"area":"rag"},{"id":"2406.05087","title":"Corpus Poisoning via Approximate Greedy Gradient Descent","created":"2024-06-07","cited_by_count":21,"area":"rag"},{"id":"2412.20953","title":"GASLITEing the Retrieval: Exploring Vulnerabilities in Dense Embedding-based Search","created":"2024-12-30","cited_by_count":20,"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":"2505.07546","title":"GRADA: Graph-based Reranking against Adversarial Documents Attack","created":"2025-05-12","cited_by_count":10,"area":"rag"},{"id":"2508.09497","title":"From Ranking to Selection: A Simple but Efficient Dynamic Passage Selector for Retrieval Augmented Generation","created":"2025-08-13","cited_by_count":6,"area":"rag"},{"id":"2501.13297","title":"RAMQA: A Unified Framework for Retrieval-Augmented Multi-Modal Question Answering","created":"2025-01-23","cited_by_count":5,"area":"rag"},{"id":"2506.00037","title":"Query Drift Compensation: Enabling Compatibility in Continual Learning of Retrieval Embedding Models","created":"2025-05-27","cited_by_count":5,"area":"rag"},{"id":"2506.10802","title":"Constructing and Evaluating Declarative RAG Pipelines in PyTerrier","created":"2025-06-12","cited_by_count":5,"area":"rag"},{"id":"2508.17858","title":"LexSemBridge: Fine-Grained Dense Representation Enhancement through Token-Aware Embedding Augmentation","created":"2025-08-25","cited_by_count":5,"area":"rag"},{"id":"2506.08276","title":"LEANN: A Low-Storage Vector Index","created":"2025-06-09","cited_by_count":4,"area":"rag"},{"id":"2402.14318","title":"Assessing generalization capability of text ranking models in Polish","created":"2024-02-22","cited_by_count":3,"area":"rag"},{"id":"2410.09662","title":"Evaluating the Effectiveness and Efficiency of Demonstration Retrievers in RAG for Coding Tasks","created":"2024-10-12","cited_by_count":2,"area":"rag"},{"id":"2506.01615","title":"IndicRAGSuite: Large-Scale Datasets and a Benchmark for Indian Language RAG Systems","created":"2025-06-02","cited_by_count":2,"area":"rag"},{"id":"2601.10644","title":"RoutIR: Fast Serving of Retrieval Pipelines for Retrieval-Augmented Generation","created":"2026-01-15","cited_by_count":1,"area":"rag"},{"id":"2605.25716","title":"An Efficient and Privacy-Preserving Architecture for Cross-Institutional Collaborative RAG","created":"2026-05-25","cited_by_count":1,"area":"rag"},{"id":"2403.14197","title":"Context Quality Matters in Training Fusion-in-Decoder for Extractive Open-Domain Question Answering","created":"2024-03-21","cited_by_count":0,"area":"rag"},{"id":"2604.07274","title":"A Systematic Study of Retrieval Pipeline Design for Retrieval-Augmented Medical Question Answering","created":"2026-04-08","cited_by_count":0,"area":"rag"},{"id":"2607.03456","title":"SentAttack: A Sentence-Level Black-Box Adversarial Attack Method for Dense Retrieval Models","created":"2026-07-03","cited_by_count":0,"area":"rag"},{"id":"2609.01325","title":"VerTox: Verifiable Reward-Guided Corpus Poisoning Against Neural Ranking Models","created":"2026-09-01","cited_by_count":0,"area":"rag"}],"next_cursor":null}