mlsanityData to 7 Oct 2026

RAG pipeline design and evaluation

706 papers1 this weekLow confidence in this grouping: the papers may belong to more than one topic, or the group may changeLow confidence in this grouping: the papers may belong to more than one topic, or the group may change · About

Keywords: rag, generation, retrieval, llms, retrieval-augmented

Key facts. RAG pipeline design and evaluation: 706 papers on arXiv since 2022 (data through 7 Oct 2026). 188 of its 706 mapped papers (27%) cite “Retrieval-Augmented Generation for Large Language Models: A Survey” (2023, arXiv 2312.10997). 69 of its 706 mapped papers (10%) cite “ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems” (2023, arXiv 2311.09476). 6 new papers 17 Sep–7 Oct.

What’s new

17 Sep – 7 Oct 2026

6 new papers, 17 Sep – 7 Oct; 1 this week.

  1. This week · 1
  2. From Chunks to Functional Evidence: Function-Aware Retrieval for EDA Documentation QA also fits: Knowledge-graph and structured-knowledge RAG
  3. Earlier · 5
  4. Mapping the RAG Landscape: A Four Axis Taxonomy of Efficiency, Defense, Interactivity, and Reasoning
  5. AGO AI Quality Gate: Evidence-First Release Decisions for Retrieval-Augmented Generation also fits: Legal and financial RAG
  6. LLM-as-a-Judge for Low-Resource Languages: Adapting Ragas and Comparative Ranking for Romanian also fits: RAG robustness and adaptive retrieval
  7. Page-Aware Retrieval-Augmented Generation for EvalLLM 2026: A Five-Variant Study on French PDFs also fits: RAG robustness and adaptive retrieval
  8. Re:CAP - Auditing Retrieval Coverage in Production RAG Pipelines also fits: RAG robustness and adaptive retrieval

Foundations

Most cited by papers here

  1. Retrieval-Augmented Generation for Large Language Models: A Survey2023cited by 188 here
  2. ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems2023cited by 69 here
  3. Ragas: Automated Evaluation of Retrieval Augmented Generation2023cited by 62 here
  4. The Power of Noise: Redefining Retrieval for RAG Systems2024cited by 52 here
  5. A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models2024cited by 49 here

Lineage

The papers this direction builds on, oldest first.

Each paper on the line cites the one before.

  1. 2020REALM: Retrieval-Augmented Language Model Pre-Trainingcited by 139 here
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 470 here
  3. 2022Atlas: Few-shot Learning with Retrieval Augmented Language Modelscited by 93 here
  4. 2023REPLUG: Retrieval-Augmented Black-Box Language Modelscited by 94 here
  5. 2023In-Context Retrieval-Augmented Language Modelscited by 92 here
  6. 2023Active Retrieval Augmented Generationcited by 58 here
  7. 2023Making Retrieval-Augmented Language Models Robust to Irrelevant Contextcited by 46 here
  8. 2023RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentationcited by 39 here
  9. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 179 here
  10. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 188 here
  11. 2024Retrieval-Augmented Generation for AI-Generated Content: A Surveycited by 46 here
  12. 2024A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Modelscited by 49 here
12 more it builds on, not in this chain
  1. 2022When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memoriescited by 93 here
  2. 2023Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergycited by 45 here
  3. 2023Benchmarking Large Language Models in Retrieval-Augmented Generationcited by 62 here
  4. 2023Ragas: Automated Evaluation of Retrieval Augmented Generationcited by 62 here
  5. 2023RA-DIT: Retrieval-Augmented Dual Instruction Tuningcited by 42 here
  6. 2023ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systemscited by 69 here
  7. 2024The Power of Noise: Redefining Retrieval for RAG Systemscited by 52 here
  8. 2024MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queriescited by 42 here
  9. 2024RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrievalcited by 43 here
  10. 2024Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexitycited by 61 here
  11. 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarizationcited by 83 here
  12. 2024Evaluation of Retrieval-Augmented Generation: A Surveycited by 41 here

The 24 most cited of 903.

Browse

30 of 706, ranked 6–35

  1. 6Retrieval-Augmented Generation for AI-Generated Content: A Survey202446
  2. 7MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries202442
  3. 8Evaluation of Retrieval-Augmented Generation: A Survey202441
  4. 9FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research202436
  5. 10Seven Failure Points When Engineering a Retrieval Augmented Generation System202430
  6. 11Corrective Retrieval Augmented Generation202429
  7. 12RAGBench: Explainable Benchmark for Retrieval-Augmented Generation Systems202425
  8. 13Blended RAG: Improving RAG (Retriever-Augmented Generation) Accuracy with Semantic Search and Hybrid Query-Based Retrievers202422
  9. 14A Survey on Retrieval-Augmented Text Generation202222
  10. 15Evaluating Retrieval Quality in Retrieval-Augmented Generation202421
All 30
  1. 16FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation202221
  2. 17Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory202318
  3. 18Bridging the Preference Gap between Retrievers and LLMs202417
  4. 19CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Models202416
  5. 20CRAG -- Comprehensive RAG Benchmark202416
  6. 21Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach202416
  7. 22Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG202415
  8. 23PipeRAG: Fast Retrieval-Augmented Generation via Algorithm-System Co-design202413
  9. 24Optimization Methods for Personalizing Large Language Models through Retrieval Augmentation202413
  10. 25A Survey on Retrieval-Augmented Text Generation for Large Language Models202412
  11. 26RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework202412
  12. 27Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely202412
  13. 28A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions202412
  14. 29AutoRAG: Automated Framework for optimization of Retrieval Augmented Generation Pipeline202412
  15. 30LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs202411
  16. 31Ragnar"ok: A Reusable RAG Framework and Baselines for TREC 2024 Retrieval-Augmented Generation Track202411
  17. 32Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language Models202311
  18. 33Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting202410
  19. 34The Chronicles of RAG: The Retriever, the Chunk and the Generator20249
  20. 35Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledge20249