{"total":48,"rows":[{"id":"2406.13629","title":"InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales","created":"2024-06-19","cited_by_count":101,"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":"2504.08748","title":"A Survey of Multimodal Retrieval-Augmented Generation","created":"2025-03-26","cited_by_count":37,"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":"2407.09252","title":"Context Embeddings for Efficient Answer Generation in RAG","created":"2024-07-12","cited_by_count":26,"area":"rag"},{"id":"2503.23895","title":"Dynamic Parametric Retrieval Augmented Generation for Test-time Knowledge Enhancement","created":"2025-03-31","cited_by_count":25,"area":"rag"},{"id":"2501.16075","title":"PISCO: Pretty Simple Compression for Retrieval-Augmented Generation","created":"2025-01-27","cited_by_count":20,"area":"rag"},{"id":"2504.14891","title":"Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive Survey","created":"2025-04-21","cited_by_count":20,"area":"rag"},{"id":"2508.01832","title":"MLP Memory: A Retriever-Pretrained Memory for Large Language Models","created":"2025-08-03","cited_by_count":20,"area":"rag"},{"id":"2503.10720","title":"AttentionRAG: Attention-Guided Context Pruning in Retrieval-Augmented Generation","created":"2025-03-13","cited_by_count":19,"area":"rag"},{"id":"2410.10293","title":"FunnelRAG: A Coarse-to-Fine Progressive Retrieval Paradigm for RAG","created":"2024-10-14","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":"2410.02719","title":"UncertaintyRAG: Span-Level Uncertainty Enhanced Long-Context Modeling for Retrieval-Augmented Generation","created":"2024-10-03","cited_by_count":16,"area":"rag"},{"id":"2505.10413","title":"Hierarchical Document Refinement for Long-context Retrieval-augmented Generation","created":"2025-05-15","cited_by_count":16,"area":"rag"},{"id":"2507.05633","title":"SARA: Selective and Adaptive Retrieval-augmented Generation with Context Compression","created":"2025-07-08","cited_by_count":10,"area":"rag"},{"id":"2604.02985","title":"Prompt Compression in the Wild: Measuring Latency, Rate Adherence, and Quality for Faster LLM Inference","created":"2026-04-03","cited_by_count":9,"area":"rag"},{"id":"2507.22931","title":"Enhancing RAG Efficiency with Adaptive Context Compression","created":"2025-07-24","cited_by_count":8,"area":"rag"},{"id":"2508.15253","title":"Conflict-Aware Soft Prompting for Retrieval-Augmented Generation","created":"2025-08-21","cited_by_count":5,"area":"rag"},{"id":"2504.07109","title":"OSCAR: Online Soft Compression And Reranking","created":"2025-03-17","cited_by_count":4,"area":"rag"},{"id":"2505.17118","title":"After Retrieval, Before Generation: Enhancing the Trustworthiness of Large Language Models in Retrieval-Augmented Generation","created":"2025-05-21","cited_by_count":4,"area":"rag"},{"id":"2505.18458","title":"A Survey of LLM $\\times$ DATA","created":"2025-05-24","cited_by_count":4,"area":"rag"},{"id":"2410.09623","title":"Quebec Automobile Insurance Question-Answering With Retrieval-Augmented Generation","created":"2024-10-12","cited_by_count":2,"area":"rag"},{"id":"2502.10976","title":"QuOTE: Question-Oriented Text Embeddings","created":"2025-02-16","cited_by_count":2,"area":"rag"},{"id":"2511.18832","title":"Concept than Document: Context Compression via AMR-based Conceptual Entropy","created":"2025-11-24","cited_by_count":2,"area":"rag"},{"id":"2601.13222","title":"Incorporating Q&A Nuggets into Retrieval-Augmented Generation","created":"2026-01-19","cited_by_count":2,"area":"rag"},{"id":"2601.18886","title":"XProvence: Zero-Cost Multilingual Context Pruning for Retrieval-Augmented Generation","created":"2026-01-26","cited_by_count":2,"area":"rag"},{"id":"2407.01403","title":"Optimization of Retrieval-Augmented Generation Context with Outlier Detection","created":"2024-07-01","cited_by_count":1,"area":"rag"},{"id":"2508.05909","title":"Beyond Perplexity: Let the Reader Select Retrieval Summaries via Spectrum Projection Score","created":"2025-08-08","cited_by_count":1,"area":"rag"},{"id":"2601.05038","title":"ArcAligner: Adaptive Recursive Aligner for Compressed Context Embeddings in RAG","created":"2026-01-08","cited_by_count":1,"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":"2602.12235","title":"Detecting Overflow in Compressed Token Representations for Retrieval-Augmented Generation","created":"2026-02-12","cited_by_count":1,"area":"rag"},{"id":"2603.08819","title":"Beyond Relevance: On the Relationship Between Retrieval and RAG Information Coverage","created":"2026-03-09","cited_by_count":1,"area":"rag"},{"id":"2604.17866","title":"Latent Abstraction for Retrieval-Augmented Generation","created":"2026-04-20","cited_by_count":1,"area":"rag"},{"id":"2604.23734","title":"Prism-Reranker: Beyond Relevance Scoring -- Jointly Producing Contributions and Evidence for Agentic Retrieval","created":"2026-04-26","cited_by_count":1,"area":"rag"},{"id":"2605.00505","title":"LLM-Oriented Information Retrieval: A Denoising-First Perspective","created":"2026-05-01","cited_by_count":1,"area":"rag"},{"id":"2605.30790","title":"On the impact of retrieved content representations in RAG Pipelines","created":"2026-05-29","cited_by_count":1,"area":"rag"},{"id":"2606.21807","title":"Fixed RAG Compression Collapses Measured Reader Scaling","created":"2026-06-20","cited_by_count":1,"area":"rag"},{"id":"2608.13588","title":"IterCOMP: Reasoning-aware Adaptive Prompt Compression for Multi-hop Question Answering","created":"2026-07-12","cited_by_count":1,"area":"rag"},{"id":"2508.01084","title":"Provably Secure Retrieval-Augmented Generation","created":"2025-08-01","cited_by_count":0,"area":"rag"},{"id":"2603.09347","title":"The Virtuous Cycle: AI-Powered Vector Search and Vector Search-Augmented AI","created":"2026-03-10","cited_by_count":0,"area":"rag"},{"id":"2604.14403","title":"A Unified Model and Document Representation for On-Device Retrieval-Augmented Generation","created":"2026-04-15","cited_by_count":0,"area":"rag"},{"id":"2604.20452","title":"HaS: Accelerating RAG through Homology-Aware Speculative Retrieval","created":"2026-04-22","cited_by_count":0,"area":"rag"},{"id":"2606.28361","title":"ConCise: Training-Free Conclusion-Chain State Compression for Cost-Efficient Multi-Step RAG Services","created":"2026-06-13","cited_by_count":0,"area":"rag"},{"id":"2608.00765","title":"RAGOCR: Optical Compression of Retrieval-Augmented Text via Visual Representation","created":"2026-08-01","cited_by_count":0,"area":"rag"},{"id":"2608.02560","title":"Structured Memory for Edge Language Models: Persistent Context and Corpus Retrieval via O(1) SSM State Injection","created":"2026-08-03","cited_by_count":0,"area":"rag"},{"id":"2609.05152","title":"Compression Beyond the Uncompressed: A Two-Stage Training Recipe for Soft Context Compression in RAG","created":"2026-09-04","cited_by_count":0,"area":"rag"},{"id":"2609.11209","title":"REVA: Reusable Evidence View Aggregation for Context-Efficient RAG Serving","created":"2026-09-10","cited_by_count":0,"area":"rag"},{"id":"2609.14245","title":"The Attribution-Compression Frontier in Retrieval-Augmented Generation","created":"2026-09-13","cited_by_count":0,"area":"rag"}],"next_cursor":null}