mlsanityData to 14 Oct 2026

Large Language Models for Information Retrieval: A Survey

arXiv 2308.07107 ↗First posted 14 Aug 2023cs.CL cs.IRcited by 331

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Cited by 53 in Retrieval-augmented generation, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

As a primary means of information acquisition, information retrieval (IR) systems, such as search engines, have integrated themselves into our daily lives. These systems also serve as components of dialogue, question-answering, and recommender systems. The trajectory of IR has evolved dynamically from its origins in term-based methods to its integration with advanced neural models. While the neural models excel at capturing complex contextual signals and semantic nuances, thereby reshaping the IR landscape, they still face challenges such as data scarcity, interpretability, and the generation of contextually plausible yet potentially inaccurate responses. This evolution requires a combination of both traditional methods (such as term-based sparse retrieval methods with rapid response) and modern neural architectures (such as language models with powerful language understanding capacity). Meanwhile, the emergence of large language models (LLMs), typified by ChatGPT and GPT-4, has revolutionized natural language processing due to their remarkable language understanding, generation, generalization, and reasoning abilities. Consequently, recent research has sought to leverage LLMs to improve IR systems. Given the rapid evolution of this research trajectory, it is necessary to consolidate existing methodologies and provide nuanced insights through a comprehensive overview. In this survey, we delve into the confluence of LLMs and IR systems, including crucial aspects such as query rewriters, retrievers, rerankers, and readers. Additionally, we explore promising directions, such as search agents, within this expanding field.

Key facts. Cited by 331 papers in the map (data through 14 Oct 2026). Builds on 164 of its 419 references that are in the map. First posted on arXiv 14 Aug 2023.

Builds on

164 of 419 references.

References · 164

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50 most cited of 164 All 164 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 15; 2024: 125; 2025: 117; 2026: 74.

331 papers.

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  3. 2023How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Compositioncited by 223
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  7. 2024MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Retrieval Augmentationcited by 119
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  9. 2024Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Eracited by 98
  10. 2024MarkLLM: An Open-Source Toolkit for LLM Watermarkingcited by 95
  11. 2024From Matching to Generation: A Survey on Generative Information Retrievalcited by 89
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38 more
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  3. 2024A Survey on Retrieval-Augmented Text Generation for Large Language Modelscited by 77
  4. 2024Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCachecited by 73
  5. 2024AvaTaR: Optimizing LLM Agents for Tool Usage via Contrastive Reasoningcited by 72
  6. 2024Vul-RAG: Enhancing LLM-based Vulnerability Detection via Knowledge-level RAGcited by 68
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  8. 2024LitLLM: A Toolkit for Scientific Literature Reviewcited by 63
  9. 2024SelfDefend: LLMs Can Defend Themselves against Jailbreaking in a Practical Mannercited by 63
  10. 2024STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Basescited by 55
  11. 2024Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answeringcited by 51
  12. 2024RaFe: Ranking Feedback Improves Query Rewriting for RAGcited by 49
  13. 2024Multicalibration for Confidence Scoring in LLMscited by 46
  14. 2023Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generatorscited by 43
  15. 2024Attention in Large Language Models Yields Efficient Zero-Shot Re-Rankerscited by 43
  16. 2025ReasonRank: Empowering Passage Ranking with Strong Reasoning Abilitycited by 42
  17. 2025Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistenciescited by 39
  18. 2023Neural Retrievers are Biased Towards LLM-Generated Contentcited by 38
  19. 2024UniMS-RAG: A Unified Multi-source Retrieval-Augmented Generation for Personalized Dialogue Systemscited by 38
  20. 2023Thought Propagation: An Analogical Approach to Complex Reasoning with Large Language Modelscited by 37
  21. 2024ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detectioncited by 37
  22. 2024Small Models, Big Insights: Leveraging Slim Proxy Models To Decide When and What to Retrieve for LLMscited by 34
  23. 2025Search Self-play: Pushing the Frontier of Agent Capability without Supervisioncited by 34
  24. 2025A Survey of Large Language Model Empowered Agents for Recommendation and Search: Towards Next-Generation Information Retrievalcited by 33
  25. 2024JMLR: Joint Medical LLM and Retrieval Training for Enhancing Reasoning and Professional Question Answering Capabilitycited by 32
  26. 2024LLMs + Persona-Plug = Personalized LLMscited by 32
  27. 2025Uncertainty Quantification for LLMs through Minimum Bayes Risk: Bridging Confidence and Consistencycited by 30
  28. 2024CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Searchcited by 29
  29. 2024APEER: Automatic Prompt Engineering Enhances Large Language Model Rerankingcited by 28
  30. 2024Exploring Large Language Models for Feature Selection: A Data-centric Perspectivecited by 27
  31. 2024Knowledge-Aware Query Expansion with Large Language Models for Textual and Relational Retrievalcited by 26
  32. 2024BASES: Large-scale Web Search User Simulation with Large Language Model based Agentscited by 25
  33. 2024Sequential Large Language Model-Based Hyper-parameter Optimizationcited by 24
  34. 2023MILL: Mutual Verification with Large Language Models for Zero-Shot Query Expansioncited by 23
  35. 2024TRAD: Enhancing LLM Agents with Step-Wise Thought Retrieval and Aligned Decisioncited by 23
  36. 2023LLM for SoC Security: A Paradigm Shiftcited by 22
  37. 2024A Survey of Conversational Searchcited by 22
  38. 2025CoLLM: A Large Language Model for Composed Image Retrievalcited by 21

50 most cited of 331 All 331 (JSON)

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