{"total":81,"rows":[{"id":"2005.11401","title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks","created":"2020-05-22","cited_by_count":9297,"area":"rag"},{"id":"2002.08909","title":"REALM: Retrieval-Augmented Language Model Pre-Training","created":"2020-02-10","cited_by_count":2141,"area":"rag"},{"id":"2405.06211","title":"A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models","created":"2024-05-10","cited_by_count":452,"area":"rag"},{"id":"2310.01558","title":"Making Retrieval-Augmented Language Models Robust to Irrelevant Context","created":"2023-10-02","cited_by_count":369,"area":"rag"},{"id":"2311.09476","title":"ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems","created":"2023-11-16","cited_by_count":265,"area":"rag"},{"id":"2305.14283","title":"Query Rewriting for Retrieval-Augmented Large Language Models","created":"2023-05-23","cited_by_count":213,"area":"rag"},{"id":"2106.05346","title":"End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering","created":"2021-06-09","cited_by_count":133,"area":"rag"},{"id":"2210.02627","title":"Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering","created":"2022-10-06","cited_by_count":127,"area":"rag"},{"id":"2203.07722","title":"ReACC: A Retrieval-Augmented Code Completion Framework","created":"2022-03-15","cited_by_count":119,"area":"rag"},{"id":"2305.02437","title":"Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory","created":"2023-05-03","cited_by_count":103,"area":"rag"},{"id":"2407.01370","title":"Summary of a Haystack: A Challenge to Long-Context LLMs and RAG Systems","created":"2024-07-01","cited_by_count":87,"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":"2304.06762","title":"Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study","created":"2023-04-13","cited_by_count":63,"area":"rag"},{"id":"2405.18414","title":"Don't Forget to Connect! Improving RAG with Graph-based Reranking","created":"2024-05-28","cited_by_count":49,"area":"rag"},{"id":"2307.02694","title":"Loss Functions and Metrics in Deep Learning","created":"2023-07-05","cited_by_count":42,"area":"rag"},{"id":"2112.08688","title":"Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks","created":"2021-12-16","cited_by_count":40,"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":"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":"2205.14704","title":"Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning","created":"2022-05-29","cited_by_count":36,"area":"rag"},{"id":"2210.16773","title":"An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Tasks","created":"2022-10-30","cited_by_count":36,"area":"rag"},{"id":"2102.04643","title":"Efficient Retrieval Augmented Generation from Unstructured Knowledge for Task-Oriented Dialog","created":"2021-02-09","cited_by_count":33,"area":"rag"},{"id":"2403.14952","title":"Evidence-Driven Retrieval Augmented Response Generation for Online Misinformation","created":"2024-03-22","cited_by_count":32,"area":"rag"},{"id":"2402.12174","title":"BIDER: Bridging Knowledge Inconsistency for Efficient Retrieval-Augmented LLMs via Key Supporting Evidence","created":"2024-02-19","cited_by_count":28,"area":"rag"},{"id":"2309.09836","title":"RECAP: Retrieval-Augmented Audio Captioning","created":"2023-09-18","cited_by_count":27,"area":"rag"},{"id":"2506.00054","title":"Retrieval-Augmented Generation: A Comprehensive Survey of Architectures, Enhancements, and Robustness Frontiers","created":"2025-05-28","cited_by_count":27,"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":"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":"2505.04847","title":"Benchmarking LLM Faithfulness in RAG with Evolving Leaderboards","created":"2025-05-07","cited_by_count":20,"area":"rag"},{"id":"2211.07067","title":"Retrieval-Augmented Generative Question Answering for Event Argument Extraction","created":"2022-11-14","cited_by_count":18,"area":"rag"},{"id":"2307.03027","title":"Improving Retrieval-Augmented Large Language Models via Data Importance Learning","created":"2023-07-06","cited_by_count":17,"area":"rag"},{"id":"2406.15264","title":"Towards Fine-Grained Citation Evaluation in Generated Text: A Comparative Analysis of Faithfulness Metrics","created":"2024-06-21","cited_by_count":17,"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":"2109.10410","title":"RETRONLU: Retrieval Augmented Task-Oriented Semantic Parsing","created":"2021-09-21","cited_by_count":15,"area":"rag"},{"id":"2203.16714","title":"End-to-End Table Question Answering via Retrieval-Augmented Generation","created":"2022-03-30","cited_by_count":14,"area":"rag"},{"id":"2310.05388","title":"GROVE: A Retrieval-augmented Complex Story Generation Framework with A Forest of Evidence","created":"2023-10-09","cited_by_count":14,"area":"rag"},{"id":"2311.04177","title":"Enhancing LLM Intelligence with ARM-RAG: Auxiliary Rationale Memory for Retrieval Augmented Generation","created":"2023-11-07","cited_by_count":14,"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":"2408.13533","title":"Pandora's Box or Aladdin's Lamp: A Comprehensive Analysis Revealing the Role of RAG Noise in Large Language Models","created":"2024-08-24","cited_by_count":13,"area":"rag"},{"id":"2406.13578","title":"Enhancing Distractor Generation for Multiple-Choice Questions with Retrieval Augmented Pretraining and Knowledge Graph Integration","created":"2024-06-19","cited_by_count":11,"area":"rag"},{"id":"2406.14783","title":"Evaluating RAG-Fusion with RAGElo: an Automated Elo-based Framework","created":"2024-06-20","cited_by_count":11,"area":"rag"},{"id":"2410.09472","title":"DRCap: Decoding CLAP Latents with Retrieval-Augmented Generation for Zero-shot Audio Captioning","created":"2024-10-12","cited_by_count":11,"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":"2406.05794","title":"RE-RAG: Improving Open-Domain QA Performance and Interpretability with Relevance Estimator in Retrieval-Augmented Generation","created":"2024-06-09","cited_by_count":10,"area":"rag"},{"id":"2408.02795","title":"Entity Retrieval for Answering Entity-Centric Questions","created":"2024-08-05","cited_by_count":10,"area":"rag"},{"id":"2407.02233","title":"Synthetic Multimodal Question Generation","created":"2024-07-02","cited_by_count":8,"area":"rag"},{"id":"2410.17783","title":"Leveraging the Domain Adaptation of Retrieval Augmented Generation Models for Question Answering and Reducing Hallucination","created":"2024-10-23","cited_by_count":8,"area":"rag"},{"id":"2406.00944","title":"A Theory for Token-Level Harmonization in Retrieval-Augmented Generation","created":"2024-06-03","cited_by_count":7,"area":"rag"},{"id":"2509.03787","title":"Evaluating the Robustness of Retrieval-Augmented Generation to Adversarial Evidence in the Health Domain","created":"2025-09-04","cited_by_count":6,"area":"rag"},{"id":"2210.06345","title":"Variational Open-Domain Question Answering","created":"2022-09-23","cited_by_count":5,"area":"rag"},{"id":"2403.19889","title":"Towards a Robust Retrieval-Based Summarization System","created":"2024-03-29","cited_by_count":5,"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":"2308.10633","title":"RaLLe: A Framework for Developing and Evaluating Retrieval-Augmented Large Language Models","created":"2023-08-21","cited_by_count":4,"area":"rag"},{"id":"2405.19670","title":"One Token Can Help! Learning Scalable and Pluggable Virtual Tokens for Retrieval-Augmented Large Language Models","created":"2024-05-30","cited_by_count":4,"area":"rag"},{"id":"2408.03623","title":"Improving Retrieval-Augmented Code Comment Generation by Retrieving for Generation","created":"2024-08-07","cited_by_count":4,"area":"rag"},{"id":"2305.15344","title":"Learning Answer Generation using Supervision from Automatic Question Answering Evaluators","created":"2023-05-24","cited_by_count":3,"area":"rag"},{"id":"2406.14277","title":"QPaug: Question and Passage Augmentation for Open-Domain Question Answering of LLMs","created":"2024-06-20","cited_by_count":3,"area":"rag"},{"id":"2410.13258","title":"How Does Knowledge Selection Help Retrieval Augmented Generation?","created":"2024-10-17","cited_by_count":3,"area":"rag"},{"id":"2505.17326","title":"VoxRAG: A Step Toward Transcription-Free RAG Systems in Spoken Question Answering","created":"2025-05-22","cited_by_count":3,"area":"rag"},{"id":"2508.15437","title":"Test-time Corpus Feedback: From Retrieval to RAG","created":"2025-08-21","cited_by_count":3,"area":"rag"},{"id":"2511.21002","title":"Knowledge Completes the Vision: A Multimodal Entity-aware Retrieval-Augmented Generation Framework for News Image Captioning","created":"2025-11-26","cited_by_count":3,"area":"rag"},{"id":"2512.01335","title":"EmoRAG: Evaluating RAG Robustness to Symbolic Perturbations","created":"2025-12-01","cited_by_count":3,"area":"rag"},{"id":"2308.08169","title":"Enhancing Performance on Seen and Unseen Dialogue Scenarios using Retrieval-Augmented End-to-End Task-Oriented System","created":"2023-08-16","cited_by_count":2,"area":"rag"},{"id":"2312.10466","title":"RIGHT: Retrieval-augmented Generation for Mainstream Hashtag Recommendation","created":"2023-12-16","cited_by_count":2,"area":"rag"},{"id":"2408.12398","title":"A Comparative Analysis of Faithfulness Metrics and Humans in Citation Evaluation","created":"2024-08-22","cited_by_count":2,"area":"rag"},{"id":"2410.03461","title":"Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval-Augmented Generation","created":"2024-10-04","cited_by_count":2,"area":"rag"},{"id":"2411.13584","title":"AddrLLM: Address Rewriting via Large Language Model on Nationwide Logistics Data","created":"2024-11-17","cited_by_count":2,"area":"rag"},{"id":"2501.13567","title":"K-COMP: Retrieval-Augmented Medical Domain Question Answering With Knowledge-Injected Compressor","created":"2025-01-23","cited_by_count":2,"area":"rag"},{"id":"2503.09249","title":"Considering Length Diversity in Retrieval-Augmented Summarization","created":"2025-03-12","cited_by_count":2,"area":"rag"},{"id":"2501.17397","title":"Leveraging In-Context Learning and Retrieval-Augmented Generation for Automatic Question Generation in Educational Domains","created":"2025-01-29","cited_by_count":1,"area":"rag"},{"id":"2505.10493","title":"DACL-RAG: Data Augmentation Strategy with Curriculum Learning for Retrieval-Augmented Generation","created":"2025-05-15","cited_by_count":1,"area":"rag"},{"id":"2605.22041","title":"RADAR: Defending RAG Dynamically against Retrieval Corruption","created":"2026-05-21","cited_by_count":1,"area":"rag"},{"id":"2307.14750","title":"Exploring Annotation-free Image Captioning with Retrieval-augmented Pseudo Sentence Generation","created":"2023-07-27","cited_by_count":0,"area":"rag"},{"id":"2408.11903","title":"Ancient Wisdom, Modern Tools: Exploring Retrieval-Augmented LLMs for Ancient Indian Philosophy","created":"2024-08-21","cited_by_count":0,"area":"rag"},{"id":"2412.00125","title":"Efficient Learning Content Retrieval with Knowledge Injection","created":"2024-11-28","cited_by_count":0,"area":"rag"},{"id":"2505.08261","title":"Enhancing Cache-Augmented Generation (CAG) with Adaptive Contextual Compression for Scalable Knowledge Integration","created":"2025-05-13","cited_by_count":0,"area":"rag"},{"id":"2512.17194","title":"MMRAG-RFT: Two-stage Reinforcement Fine-tuning for Explainable Multi-modal Retrieval-augmented Generation","created":"2025-12-19","cited_by_count":0,"area":"rag"},{"id":"2605.01078","title":"A Sentence Relation-Based Approach to Sanitizing Malicious Instructions","created":"2026-05-01","cited_by_count":0,"area":"rag"},{"id":"2606.17430","title":"CIAN: Multi-Stage Framework for Event-Enriched Image Captioning via Retrieval-Augmented Generation","created":"2026-06-16","cited_by_count":0,"area":"rag"},{"id":"2608.19526","title":"Automated Summarization of Financial News Using Large Language Models and Retrieval-Augmented Generation: An Early Empirical Study (Fall 2023)","created":"2026-08-20","cited_by_count":0,"area":"rag"}],"next_cursor":null}