{"total":277,"rows":[{"id":"2005.11401","title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks","created":"2020-05-22","cited_by_count":9297,"area":"rag"},{"id":"2212.10511","title":"When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories","created":"2022-12-20","cited_by_count":1128,"area":"rag"},{"id":"2401.00396","title":"RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models","created":"2023-12-31","cited_by_count":283,"area":"rag"},{"id":"2402.07867","title":"PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models","created":"2024-02-12","cited_by_count":267,"area":"rag"},{"id":"2310.04408","title":"RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation","created":"2023-10-06","cited_by_count":256,"area":"rag"},{"id":"2501.09136","title":"Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG","created":"2025-01-15","cited_by_count":249,"area":"rag"},{"id":"2407.02485","title":"RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs","created":"2024-07-02","cited_by_count":202,"area":"rag"},{"id":"2310.01352","title":"RA-DIT: Retrieval-Augmented Dual Instruction Tuning","created":"2023-10-02","cited_by_count":195,"area":"rag"},{"id":"2405.13792","title":"xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token","created":"2024-05-22","cited_by_count":125,"area":"rag"},{"id":"2409.05591","title":"MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Retrieval Augmentation","created":"2024-09-09","cited_by_count":119,"area":"rag"},{"id":"2407.11005","title":"RAGBench: Explainable Benchmark for Retrieval-Augmented Generation Systems","created":"2024-06-25","cited_by_count":117,"area":"rag"},{"id":"2406.05870","title":"Machine Against the RAG: Jamming Retrieval-Augmented Generation with Blocker Documents","created":"2024-06-09","cited_by_count":102,"area":"rag"},{"id":"2406.04744","title":"CRAG -- Comprehensive RAG Benchmark","created":"2024-06-07","cited_by_count":97,"area":"rag"},{"id":"2401.10225","title":"ChatQA: Surpassing GPT-4 on Conversational QA and RAG","created":"2024-01-18","cited_by_count":90,"area":"rag"},{"id":"2406.00083","title":"BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models","created":"2024-06-03","cited_by_count":86,"area":"rag"},{"id":"2407.15831","title":"NV-Retriever: Improving text embedding models with effective hard-negative mining","created":"2024-07-22","cited_by_count":84,"area":"rag"},{"id":"2407.01219","title":"Searching for Best Practices in Retrieval-Augmented Generation","created":"2024-07-01","cited_by_count":83,"area":"rag"},{"id":"2405.13401","title":"TrojanRAG: Retrieval-Augmented Generation Can Be Backdoor Driver in Large Language Models","created":"2024-05-22","cited_by_count":67,"area":"rag"},{"id":"2409.14924","title":"Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely","created":"2024-09-23","cited_by_count":66,"area":"rag"},{"id":"2310.07554","title":"A Multi-Task Embedder For Retrieval Augmented LLMs","created":"2023-10-11","cited_by_count":64,"area":"rag"},{"id":"2407.09014","title":"CompAct: Compressing Retrieved Documents Actively for Question Answering","created":"2024-07-12","cited_by_count":64,"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":"2406.19417","title":"\"Glue pizza and eat rocks\" -- Exploiting Vulnerabilities in Retrieval-Augmented Generative Models","created":"2024-06-26","cited_by_count":60,"area":"rag"},{"id":"2405.20485","title":"Phantom: General Backdoor Attacks on Retrieval Augmented Language Generation","created":"2024-05-30","cited_by_count":49,"area":"rag"},{"id":"2310.14696","title":"Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language Models","created":"2023-10-23","cited_by_count":43,"area":"rag"},{"id":"2410.13070","title":"Is Semantic Chunking Worth the Computational Cost?","created":"2024-10-16","cited_by_count":43,"area":"rag"},{"id":"2502.01113","title":"GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation","created":"2025-02-03","cited_by_count":40,"area":"rag"},{"id":"2408.01262","title":"RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework","created":"2024-08-02","cited_by_count":39,"area":"rag"},{"id":"2504.03957","title":"Practical Poisoning Attacks against Retrieval-Augmented Generation","created":"2025-04-04","cited_by_count":36,"area":"rag"},{"id":"2502.17125","title":"LettuceDetect: A Hallucination Detection Framework for RAG Applications","created":"2025-02-24","cited_by_count":34,"area":"rag"},{"id":"2410.13509","title":"RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewards","created":"2024-10-17","cited_by_count":33,"area":"rag"},{"id":"2502.01386","title":"Topic-FlipRAG: Topic-Orientated Adversarial Opinion Manipulation Attacks to Retrieval-Augmented Generation Models","created":"2025-02-03","cited_by_count":33,"area":"rag"},{"id":"2406.16828","title":"Ragnar\\\"ok: A Reusable RAG Framework and Baselines for TREC 2024 Retrieval-Augmented Generation Track","created":"2024-06-24","cited_by_count":32,"area":"rag"},{"id":"2504.07717","title":"PR-Attack: Coordinated Prompt-RAG Attacks on Retrieval-Augmented Generation in Large Language Models via Bilevel Optimization","created":"2025-04-10","cited_by_count":32,"area":"rag"},{"id":"2407.01102","title":"BERGEN: A Benchmarking Library for Retrieval-Augmented Generation","created":"2024-07-01","cited_by_count":31,"area":"rag"},{"id":"2502.06872","title":"Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey","created":"2025-02-08","cited_by_count":30,"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":"2410.20142","title":"Mask-based Membership Inference Attacks for Retrieval-Augmented Generation","created":"2024-10-26","cited_by_count":29,"area":"rag"},{"id":"2411.09607","title":"Initial Nugget Evaluation Results for the TREC 2024 RAG Track with the AutoNuggetizer Framework","created":"2024-11-14","cited_by_count":28,"area":"rag"},{"id":"2504.21668","title":"Traceback of Poisoning Attacks to Retrieval-Augmented Generation","created":"2025-04-30","cited_by_count":28,"area":"rag"},{"id":"2505.11548","title":"One Shot Dominance: Knowledge Poisoning Attack on Retrieval-Augmented Generation Systems","created":"2025-05-15","cited_by_count":28,"area":"rag"},{"id":"2407.01463","title":"Retrieval-augmented generation in multilingual settings","created":"2024-07-01","cited_by_count":27,"area":"rag"},{"id":"2410.20878","title":"AutoRAG: Automated Framework for optimization of Retrieval Augmented Generation Pipeline","created":"2024-10-28","cited_by_count":27,"area":"rag"},{"id":"2410.22832","title":"HijackRAG: Hijacking Attacks against Retrieval-Augmented Large Language Models","created":"2024-10-30","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":"2406.09815","title":"Retrieval Augmented Fact Verification by Synthesizing Contrastive Arguments","created":"2024-06-14","cited_by_count":25,"area":"rag"},{"id":"2501.02968","title":"FlippedRAG: Black-Box Opinion Manipulation Adversarial Attacks to Retrieval-Augmented Generation Models","created":"2025-01-06","cited_by_count":25,"area":"rag"},{"id":"2501.14050","title":"GraphRAG under Fire","created":"2025-01-23","cited_by_count":24,"area":"rag"},{"id":"2503.01478","title":"SePer: Measure Retrieval Utility Through The Lens Of Semantic Perplexity Reduction","created":"2025-03-03","cited_by_count":24,"area":"rag"},{"id":"2403.19216","title":"Are Large Language Models Good at Utility Judgments?","created":"2024-03-28","cited_by_count":22,"area":"rag"},{"id":"2410.14479","title":"Backdoored Retrievers for Prompt Injection Attacks on Retrieval Augmented Generation of Large Language Models","created":"2024-10-18","cited_by_count":22,"area":"rag"},{"id":"2510.16724","title":"A Comprehensive Survey on Reinforcement Learning-based Agentic Search: Foundations, Roles, Optimizations, Evaluations, and Applications","created":"2025-10-19","cited_by_count":22,"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":"2402.11891","title":"FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation","created":"2024-02-19","cited_by_count":19,"area":"rag"},{"id":"2405.18111","title":"ATM: Adversarial Tuning Multi-agent System Makes a Robust Retrieval-Augmented Generator","created":"2024-05-28","cited_by_count":19,"area":"rag"},{"id":"2503.14649","title":"RAGO: Systematic Performance Optimization for Retrieval-Augmented Generation Serving","created":"2025-03-18","cited_by_count":19,"area":"rag"},{"id":"2510.25025","title":"Secure Retrieval-Augmented Generation against Poisoning Attacks","created":"2025-10-28","cited_by_count":19,"area":"rag"},{"id":"2505.18543","title":"Benchmarking Poisoning Attacks against Retrieval-Augmented Generation","created":"2025-05-24","cited_by_count":18,"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":"2412.12775","title":"RemoteRAG: A Privacy-Preserving LLM Cloud RAG Service","created":"2024-12-17","cited_by_count":17,"area":"rag"},{"id":"2505.19864","title":"CPA-RAG:Covert Poisoning Attacks on Retrieval-Augmented Generation in Large Language Models","created":"2025-05-26","cited_by_count":17,"area":"rag"},{"id":"2503.05037","title":"Collapse of Dense Retrievers: Short, Early, and Literal Biases Outranking Factual Evidence","created":"2025-03-06","cited_by_count":16,"area":"rag"},{"id":"2506.06151","title":"Joint-GCG: Unified Gradient-Based Poisoning Attacks on Retrieval-Augmented Generation Systems","created":"2025-06-06","cited_by_count":16,"area":"rag"},{"id":"2402.11573","title":"BGE Landmark Embedding: A Chunking-Free Embedding Method For Retrieval Augmented Long-Context Large Language Models","created":"2024-02-18","cited_by_count":15,"area":"rag"},{"id":"2502.04176","title":"MRAMG-Bench: A Comprehensive Benchmark for Advancing Multimodal Retrieval-Augmented Multimodal Generation","created":"2025-02-06","cited_by_count":15,"area":"rag"},{"id":"2505.15872","title":"InfoDeepSeek: Benchmarking Agentic Information Seeking for Retrieval-Augmented Generation","created":"2025-05-21","cited_by_count":15,"area":"rag"},{"id":"2409.17275","title":"On the Vulnerability of Applying Retrieval-Augmented Generation within Knowledge-Intensive Application Domains","created":"2024-09-12","cited_by_count":14,"area":"rag"},{"id":"2410.13716","title":"MIRAGE-Bench: Automatic Multilingual Benchmark Arena for Retrieval-Augmented Generation Systems","created":"2024-10-17","cited_by_count":14,"area":"rag"},{"id":"2412.16708","title":"Towards More Robust Retrieval-Augmented Generation: Evaluating RAG Under Adversarial Poisoning Attacks","created":"2024-12-21","cited_by_count":14,"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":"2504.19754","title":"Reconstructing Context: Evaluating Advanced Chunking Strategies for Retrieval-Augmented Generation","created":"2025-04-28","cited_by_count":13,"area":"rag"},{"id":"2510.09710","title":"SeCon-RAG: A Two-Stage Semantic Filtering and Conflict-Free Framework for Trustworthy RAG","created":"2025-10-10","cited_by_count":13,"area":"rag"},{"id":"2402.13482","title":"Retrieval-Augmented Data Augmentation for Low-Resource Domain Tasks","created":"2024-02-21","cited_by_count":12,"area":"rag"},{"id":"2502.10673","title":"Dataset Protection via Watermarked Canaries in Retrieval-Augmented LLMs","created":"2025-02-15","cited_by_count":12,"area":"rag"},{"id":"2504.09593","title":"ControlNET: A Firewall for RAG-based LLM System","created":"2025-04-13","cited_by_count":12,"area":"rag"},{"id":"2509.13772","title":"Who Taught the Lie? Responsibility Attribution for Poisoned Knowledge in Retrieval-Augmented Generation","created":"2025-09-17","cited_by_count":12,"area":"rag"},{"id":"2502.15025","title":"Is Relevance Propagated from Retriever to Generator in RAG?","created":"2025-02-20","cited_by_count":11,"area":"rag"},{"id":"2504.08231","title":"Out of Style: RAG's Fragility to Linguistic Variation","created":"2025-04-11","cited_by_count":11,"area":"rag"},{"id":"2504.17137","title":"MIRAGE: A Metric-Intensive Benchmark for Retrieval-Augmented Generation Evaluation","created":"2025-04-23","cited_by_count":11,"area":"rag"},{"id":"2508.02835","title":"Defending Against Knowledge Poisoning Attacks During Retrieval-Augmented Generation","created":"2025-08-04","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":"2310.13682","title":"Optimizing Retrieval-augmented Reader Models via Token Elimination","created":"2023-10-20","cited_by_count":10,"area":"rag"},{"id":"2402.13542","title":"ARL2: Aligning Retrievers for Black-box Large Language Models via Self-guided Adaptive Relevance Labeling","created":"2024-02-21","cited_by_count":10,"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":"2505.18583","title":"The Silent Saboteur: Imperceptible Adversarial Attacks against Black-Box Retrieval-Augmented Generation Systems","created":"2025-05-24","cited_by_count":10,"area":"rag"},{"id":"2505.00263","title":"EnronQA: Towards Personalized RAG over Private Documents","created":"2025-05-01","cited_by_count":9,"area":"rag"},{"id":"2505.03075","title":"Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models","created":"2025-05-05","cited_by_count":9,"area":"rag"},{"id":"2506.11063","title":"Who is in the Spotlight: The Hidden Bias Undermining Multimodal Retrieval-Augmented Generation","created":"2025-05-30","cited_by_count":9,"area":"rag"},{"id":"2506.20051","title":"Controlled Retrieval-augmented Context Evaluation for Long-form RAG","created":"2025-06-24","cited_by_count":9,"area":"rag"},{"id":"2511.01268","title":"Rescuing the Unpoisoned: Efficient Defense against Knowledge Corruption Attacks on RAG Systems","created":"2025-11-03","cited_by_count":9,"area":"rag"},{"id":"2605.05253","title":"EnterpriseRAG-Bench: A RAG Benchmark for Company Internal Knowledge","created":"2026-05-05","cited_by_count":9,"area":"rag"},{"id":"2407.19794","title":"Introducing a new hyper-parameter for RAG: Context Window Utilization","created":"2024-07-29","cited_by_count":8,"area":"rag"},{"id":"2411.19710","title":"Know Your RAG: Dataset Taxonomy and Generation Strategies for Evaluating RAG Systems","created":"2024-11-29","cited_by_count":8,"area":"rag"},{"id":"2502.18817","title":"Judge as A Judge: Improving the Evaluation of Retrieval-Augmented Generation through the Judge-Consistency of Large Language Models","created":"2025-02-26","cited_by_count":8,"area":"rag"},{"id":"2504.02921","title":"HyperRAG: Enhancing Quality-Efficiency Tradeoffs in Retrieval-Augmented Generation with Reranker KV-Cache Reuse","created":"2025-04-03","cited_by_count":8,"area":"rag"},{"id":"2509.12765","title":"InfoGain-RAG: Boosting Retrieval-Augmented Generation via Document Information Gain-based Reranking and Filtering","created":"2025-09-16","cited_by_count":8,"area":"rag"},{"id":"2512.25052","title":"AdaGReS:Adaptive Greedy Context Selection via Redundancy-Aware Scoring for Token-Budgeted RAG","created":"2025-12-31","cited_by_count":8,"area":"rag"},{"id":"2403.00982","title":"LocalRQA: From Generating Data to Locally Training, Testing, and Deploying Retrieval-Augmented QA Systems","created":"2024-03-01","cited_by_count":7,"area":"rag"}],"next_cursor":"100"}