mlsanityData to 13 Oct 2026

AutoRAG: Automated Framework for optimization of Retrieval Augmented Generation Pipeline

arXiv 2410.20878 ↗First posted 28 Oct 2024cs.CLcited by 27

On the map: Retrieval-augmented generation → RAG pipeline design and evaluation

Abstract (arXiv)

Using LLMs (Large Language Models) in conjunction with external documents has made RAG (Retrieval-Augmented Generation) an essential technology. Numerous techniques and modules for RAG are being researched, but their performance can vary across different datasets. Finding RAG modules that perform well on specific datasets is challenging. In this paper, we propose the AutoRAG framework, which automatically identifies suitable RAG modules for a given dataset. AutoRAG explores and approximates the optimal combination of RAG modules for the dataset. Additionally, we share the results of optimizing a dataset using AutoRAG. All experimental results and data are publicly available and can be accessed through our GitHub repository https://github.com/Marker-Inc-Korea/AutoRAG_ARAGOG_Paper .

Key facts. Cited by 27 papers in the map (data through 13 Oct 2026). Placed in RAG pipeline design and evaluation, one of 15 directions in Retrieval-augmented generation. Builds on 17 of its 24 references that are in the map. First posted on arXiv 28 Oct 2024.

Builds on

17 of 24 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024Modular RAG: Transforming RAG Systems into LEGO-like Reconfigurable Frameworks26 Jul
  2. 2023Retrieval-Augmented Generation for Large Language Models: A Survey18 Dec

Other references · 15

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,549
  2. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,916
  3. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,797
  4. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,412
  5. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,228
  6. 2016MS MARCO: A Human Generated MAchine Reading COmprehension Datasetcited by 1,600
  7. 2020ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERTcited by 1,169
  8. 2022Precise Zero-Shot Dense Retrieval without Relevance Labelscited by 510
  9. 2020Document Ranking with a Pretrained Sequence-to-Sequence Modelcited by 375
  10. 2023Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agentscited by 358
  11. 2022Improving Passage Retrieval with Zero-Shot Question Generationcited by 165
  12. 2021Mr. TyDi: A Multi-lingual Benchmark for Dense Retrievalcited by 119
3 more
  1. 2022Task-aware Retrieval with Instructionscited by 107
  2. 2022An Analysis of Fusion Functions for Hybrid Retrievalcited by 50
  3. 2024SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similaritycited by 19

Built on by

Cited by year (2026 to 13 Oct)

Citing papers per year: 2024: 1; 2025: 15; 2026: 11.

27 papers.

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  1. 2025Memory in the Age of AI Agentscited by 291
  2. 2025A Survey on the Optimization of Large Language Model-based Agentscited by 46
  3. 2025MCTS-RAG: Enhancing Retrieval-Augmented Generation with Monte Carlo Tree Searchcited by 21
  4. 2024METIS: Fast Quality-Aware RAG Systems with Configuration Adaptationcited by 16
  5. 2025AdaVideoRAG: Omni-Contextual Adaptive Retrieval-Augmented Efficient Long Video Understandingcited by 15
  6. 2025RaCoT: Plug-and-Play Contrastive Example Generation Mechanism for Enhanced LLM Reasoning Reliabilitycited by 14
  7. 2025Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generationcited by 13
  8. 2025Faster, Cheaper, Better: Multi-Objective Hyperparameter Optimization for LLM and RAG Systemscited by 11
  9. 2025syftr: Pareto-Optimal Generative AIcited by 5
  10. 2025RAGSmith: A Framework for Finding the Optimal Composition of Retrieval-Augmented Generation Methods Across Datasetscited by 5
  11. 2026C2KV: Compressed and Composable KV Cache Reuse for Efficient LLM Inferencecited by 3
  12. 2025Urban Computing in the Era of Large Language Modelscited by 2
15 more
  1. 2025An Analysis of Hyper-Parameter Optimization Methods for Retrieval Augmented Generationcited by 2
  2. 2025FlexRAG: A Flexible and Comprehensive Framework for Retrieval-Augmented Generationcited by 2
  3. 2025Single LLM, Multiple Roles: A Unified Retrieval-Augmented Generation Framework Using Role-Specific Token Optimizationcited by 1
  4. 2025Domain-Specific Data Generation Framework for RAG Adaptationcited by 1
  5. 2026RAGTurk: Best Practices for Retrieval Augmented Generation in Turkishcited by 1
  6. 2026LLM-Oriented Information Retrieval: A Denoising-First Perspectivecited by 1
  7. 2026AutoRAGTuner: A Declarative Framework for Automatic Optimization of RAG Pipelinescited by 1
  8. 2025The Other Side of the Coin: Exploring Fairness in Retrieval-Augmented Generationcited by 0
  9. 2026LogicGaze: Benchmarking Causal Consistency in Visual Narratives via Counterfactual Verificationcited by 0
  10. 2026LatentRAG: Latent Reasoning and Retrieval for Efficient Agentic RAGcited by 0
  11. 2026RAISE: RAG Design as an Architecture Search Problemcited by 0
  12. 2026An Agentic Framework Using Rules and LLMs for Embedding and Annotating Descriptive Document Layouts: A Plant Science Use Casecited by 0
  13. 2026UniK: Universal Knowledge Perception for Digital and Physical AIcited by 0
  14. 2026STITCH-RAG: Spatio-Temporal Influence Tracing over Topic Hypergraphs for Multi-Hop Retrieval-Augmented Generationcited by 0
  15. 2026Agentic AutoRAG: RAG Pipeline Optimization through Reasoning-Driven Agentscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024XRAG: eXamining the Core -- Benchmarking Foundational Components in Advanced Retrieval-Augmented Generation
  2. 2024FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research
  3. 2024RAG Foundry: A Framework for Enhancing LLMs for Retrieval Augmented Generation
  4. 2025UltraRAG: A Modular and Automated Toolkit for Adaptive Retrieval-Augmented Generation
  5. 2024Towards Optimizing a Retrieval Augmented Generation using Large Language Model on Academic Data
  6. 2025mmRAG: A Modular Benchmark for Retrieval-Augmented Generation over Text, Tables, and Knowledge Graphs
  7. 2025RAG-Stack: Co-Optimizing RAG Quality and Performance From the Vector Database Perspective
  8. 2025Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive Survey