mlsanityData to 7 Oct 2026

A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions

arXiv 2410.12837 ↗First posted 3 Oct 2024cs.CL cs.AI cs.IRcited by 69

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

Abstract (arXiv)

This paper presents a comprehensive study of Retrieval-Augmented Generation (RAG), tracing its evolution from foundational concepts to the current state of the art. RAG combines retrieval mechanisms with generative language models to enhance the accuracy of outputs, addressing key limitations of LLMs. The study explores the basic architecture of RAG, focusing on how retrieval and generation are integrated to handle knowledge-intensive tasks. A detailed review of the significant technological advancements in RAG is provided, including key innovations in retrieval-augmented language models and applications across various domains such as question-answering, summarization, and knowledge-based tasks. Recent research breakthroughs are discussed, highlighting novel methods for improving retrieval efficiency. Furthermore, the paper examines ongoing challenges such as scalability, bias, and ethical concerns in deployment. Future research directions are proposed, focusing on improving the robustness of RAG models, expanding the scope of application of RAG models, and addressing societal implications. This survey aims to serve as a foundational resource for researchers and practitioners in understanding the potential of RAG and its trajectory in natural language processing.

Key facts. Cited by 69 papers in the map (data through 7 Oct 2026). Placed in RAG pipeline design and evaluation, one of 15 directions in Retrieval-augmented generation. Builds on 11 of its 11 references that are in the map. First posted on arXiv 3 Oct 2024.

Builds on

11 of 11 references.

References · 11

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  3. 2014Sequence to Sequence Learning with Neural Networkscited by 2,974
  4. 2015Learning both Weights and Connections for Efficient Neural Networkscited by 1,998
  5. 2024RAFT: Adapting Language Model to Domain Specific RAGcited by 258
  6. 2022Retrieval-Augmented Multimodal Language Modelingcited by 125
  7. 2023Llama2Vec: Unsupervised Adaptation of Large Language Models for Dense Retrievalcited by 77
  8. 2023Cross-Modal Retrieval: A Systematic Review of Methods and Future Directionscited by 40
  9. 2023TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Predictioncited by 23
  10. 2023"Knowing When You Don't Know": A Multilingual Relevance Assessment Dataset for Robust Retrieval-Augmented Generationcited by 12
  11. 2024LA-RAG:Enhancing LLM-based ASR Accuracy with Retrieval-Augmented Generationcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 44; 2026: 23.

69 papers.

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  1. 2025Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systemscited by 125
  2. 2025StepSearch: Igniting LLMs Search Ability via Step-Wise Proximal Policy Optimizationcited by 82
  3. 2025Retrieval Augmented Generation and Understanding in Vision: A Survey and New Outlookcited by 32
  4. 2025Solving Inequality Proofs with Large Language Modelscited by 21
  5. 2025Optimizing the Interface Between Knowledge Graphs and LLMs for Complex Reasoningcited by 17
  6. 2025RaCoT: Plug-and-Play Contrastive Example Generation Mechanism for Enhanced LLM Reasoning Reliabilitycited by 14
  7. 2025Poisoned-MRAG: Knowledge Poisoning Attacks to Multimodal Retrieval Augmented Generationcited by 12
  8. 2025Reconstructing Context: Evaluating Advanced Chunking Strategies for Retrieval-Augmented Generationcited by 12
  9. 2025CoT-RAG: Integrating Chain of Thought and Retrieval-Augmented Generation to Enhance Reasoning in Large Language Modelscited by 8
  10. 2025GLARE: Agentic Reasoning for Legal Judgment Predictioncited by 6
  11. 2025Rethinking Retrieval-Augmented Generation for Medicine: A Large-Scale, Systematic Expert Evaluation and Practical Insightscited by 6
  12. 2025mmRAG: A Modular Benchmark for Retrieval-Augmented Generation over Text, Tables, and Knowledge Graphscited by 5
38 more
  1. 2025Demystifying and Enhancing the Efficiency of Large Language Model Based Search Agentscited by 5
  2. 2025CFT-RAG: An Entity Tree Based Retrieval Augmented Generation Algorithm With Cuckoo Filtercited by 4
  3. 2025Less LLM, More Documents: Searching for Improved RAGcited by 4
  4. 2025Generative AI Enhanced Financial Risk Management Information Retrievalcited by 3
  5. 2025Engineering RAG Systems for Real-World Applications: Design, Development, and Evaluationcited by 3
  6. 2025ILRe: Intermediate Layer Retrieval for Context Compression in Causal Language Modelscited by 3
  7. 2025Comprehensive Framework for Evaluating Conversational AI Chatbotscited by 2
  8. 2025Investigating Retrieval-Augmented Generation in Quranic Studies: A Study of 13 Open-Source Large Language Modelscited by 2
  9. 2025ZKPROV: A Zero-Knowledge Approach to Dataset Provenance for Large Language Modelscited by 2
  10. 2026RAGExplorer: A Visual Analytics System for the Comparative Diagnosis of RAG Systemscited by 2
  11. 2026LURE-RAG: Lightweight Utility-driven Reranking for Efficient RAGcited by 2
  12. 2024A Survey of Query Optimization in Large Language Modelscited by 1
  13. 2025Cognitive-Aligned Document Selection for Retrieval-augmented Generationcited by 1
  14. 2025FinBloom: Knowledge Grounding Large Language Model with Real-time Financial Datacited by 1
  15. 2025Taxonomic Reasoning for Rare Arthropods: Combining Dense Image Captioning and RAG for Interpretable Classificationcited by 1
  16. 2025Agent-Enhanced Large Language Models for Researching Political Institutionscited by 1
  17. 2025Agentic Multimodal AI for Hyperpersonalized B2B and B2C Advertising in Competitive Markets: An AI-Driven Competitive Advertising Frameworkcited by 1
  18. 2025Less Context, Same Performance: A RAG Framework for Resource-Efficient LLM-Based Clinical NLPcited by 1
  19. 2025Development and Evaluation of HopeBot: an LLM-based chatbot for structured and interactive PHQ-9 depression screeningcited by 1
  20. 2025Retrieval-Augmented Generation for Reliable Interpretation of Radio Regulationscited by 1
  21. 2025Human-Centered Evaluation of RAG outputs: a framework and questionnaire for human-AI collaborationcited by 1
  22. 2025Leveraging Spreading Activation for Improved Document Retrieval in Knowledge-Graph-Based RAG Systemscited by 1
  23. 2026ProtRLSearch: A Multi-Round Multimodal Protein Search Agent with Large Language Models Trained via Reinforcement Learningcited by 1
  24. 2026Leveraging LLM Parametric Knowledge for Fact Checking without Retrievalcited by 1
  25. 2026DOTRAG: Retrieval-Time Reasoning Along Pathscited by 1
  26. 2026Light-Omni: Reflex over Reasoning in Agentic Video Understanding with Long-Term Memorycited by 1
  27. 2026Bridging the Question-Answer Gap in Retrieval-Augmented Generation: Hypothetical Prompt Embeddingscited by 1
  28. 2024PersianRAG: A Retrieval-Augmented Generation System for Persian Languagecited by 0
  29. 2025Wormhole Memory: A Rubik's Cube for Cross-Dialogue Retrievalcited by 0
  30. 2025Towards Efficient Educational Chatbots: Benchmarking RAG Frameworkscited by 0
  31. 2025Performance and Practical Considerations of Large and Small Language Models in Clinical Decision Support in Rheumatologycited by 0
  32. 2025MultiFluxAI Enhancing Platform Engineering with Advanced Agent-Orchestrated Retrieval Systemscited by 0
  33. 2025Towards End-to-End Model-Agnostic Explanations for RAG Systemscited by 0
  34. 2025Reconsidering Requirements Engineering: Human-AI Collaboration in AI-Native Software Developmentcited by 0
  35. 2025MHA-RAG: Improving Efficiency, Accuracy, and Consistency by Encoding Exemplars as Soft Promptscited by 0
  36. 2025M-Eval: A Heterogeneity-Based Framework for Multi-evidence Validation in Medical RAG Systemscited by 0
  37. 2025Hybrid Retrieval-Augmented Generation Agent for Trustworthy Legal Question Answering in Judicial Forensicscited by 0
  38. 2025Search Is Not Retrieval: Decoupling Semantic Matching from Contextual Assembly in RAGcited by 0

50 most cited of 69 All 69 (JSON)

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  1. 2025A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions
  2. 2025A Survey on Knowledge-Oriented Retrieval-Augmented Generation
  3. 2025Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive Survey
  4. 2024Evaluation of Retrieval-Augmented Generation: A Survey
  5. 2024Retrieval-Augmented Generation for Natural Language Processing: A Survey
  6. 2025When Retrieval Succeeds and Fails: Rethinking Retrieval-Augmented Generation for LLMs
  7. 2024A Survey on Retrieval-Augmented Text Generation for Large Language Models
  8. 2025Enhancing Retrieval-Augmented Generation: A Study of Best Practices