mlsanityData to 14 Oct 2026

Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Search

arXiv 2303.06573 ↗First posted 12 Mar 2023cs.IRcited by 75

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Abstract (arXiv)

Precisely understanding users' contextual search intent has been an important challenge for conversational search. As conversational search sessions are much more diverse and long-tailed, existing methods trained on limited data still show unsatisfactory effectiveness and robustness to handle real conversational search scenarios. Recently, large language models (LLMs) have demonstrated amazing capabilities for text generation and conversation understanding. In this work, we present a simple yet effective prompting framework, called LLM4CS, to leverage LLMs as a text-based search intent interpreter to help conversational search. Under this framework, we explore three prompting methods to generate multiple query rewrites and hypothetical responses, and propose to aggregate them into an integrated representation that can robustly represent the user's real contextual search intent. Extensive automatic evaluations and human evaluations on three widely used conversational search benchmarks, including CAsT-19, CAsT-20, and CAsT-21, demonstrate the remarkable performance of our simple LLM4CS framework compared with existing methods and even using human rewrites. Our findings provide important evidence to better understand and leverage LLMs for conversational search.

Key facts. Cited by 75 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Mar 2023.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 11; 2024: 32; 2025: 21; 2026: 11.

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  1. 2024Retrieval-Augmented Generation for AI-Generated Content: A Surveycited by 354
  2. 2023Large Language Models for Information Retrieval: A Surveycited by 331
  3. 2023Video Understanding with Large Language Models: A Surveycited by 206
  4. 2023ConvGQR: Generative Query Reformulation for Conversational Searchcited by 59
  5. 2024Re-Invoke: Tool Invocation Rewriting for Zero-Shot Tool Retrievalcited by 52
  6. 2023RETA-LLM: A Retrieval-Augmented Large Language Model Toolkitcited by 40
  7. 2025Rec-R1: Bridging Generative Large Language Models and User-Centric Recommendation Systems via Reinforcement Learningcited by 33
  8. 2024Grounding Language Model with Chunking-Free In-Context Retrievalcited by 30
  9. 2024CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Searchcited by 29
  10. 2024VideoINSTA: Zero-shot Long Video Understanding via Informative Spatial-Temporal Reasoning with LLMscited by 29
  11. 2023Learning to Relate to Previous Turns in Conversational Searchcited by 26
  12. 2023MILL: Mutual Verification with Large Language Models for Zero-Shot Query Expansioncited by 23
38 more
  1. 2024Ask Optimal Questions: Aligning Large Language Models with Retriever's Preference in Conversationcited by 23
  2. 2024A Survey of Conversational Searchcited by 22
  3. 2024INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuningcited by 20
  4. 2024ChatRetriever: Adapting Large Language Models for Generalized and Robust Conversational Dense Retrievalcited by 19
  5. 2024Enhancing Interactive Image Retrieval With Query Rewriting Using Large Language Models and Vision Language Modelscited by 19
  6. 2023GAR-meets-RAG Paradigm for Zero-Shot Information Retrievalcited by 18
  7. 2024Generalizing Conversational Dense Retrieval via LLM-Cognition Data Augmentationcited by 17
  8. 2025Thought-Augmented Planning for LLM-Powered Interactive Recommender Agentcited by 17
  9. 2024Learning Interpretable Legal Case Retrieval via Knowledge-Guided Case Reformulationcited by 15
  10. 2024AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignmentcited by 14
  11. 2025UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversationscited by 12
  12. 2023Synergistic Interplay between Search and Large Language Models for Information Retrievalcited by 11
  13. 2024How to Leverage Personal Textual Knowledge for Personalized Conversational Information Retrievalcited by 11
  14. 2024Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Searchcited by 11
  15. 2024AMPO: Automatic Multi-Branched Prompt Optimizationcited by 11
  16. 2024Learning When to Retrieve, What to Rewrite, and How to Respond in Conversational QAcited by 9
  17. 2024DiSCo: LLM Knowledge Distillation for Efficient Sparse Retrieval in Conversational Searchcited by 9
  18. 2024ConvSDG: Session Data Generation for Conversational Searchcited by 8
  19. 2024Toward Conversational Agents with Context and Time Sensitive Long-term Memorycited by 8
  20. 2024CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation Generationcited by 8
  21. 2025Conversational Search: From Fundamentals to Frontiers in the LLM Eracited by 8
  22. 2024Blind Spot Navigation in Large Language Model Reasoning with Thought Space Explorercited by 7
  23. 2025SpatialPrompting: Keyframe-driven Zero-Shot Spatial Reasoning with Off-the-Shelf Multimodal Large Language Modelscited by 7
  24. 2024RRADistill: Distilling LLMs' Passage Ranking Ability for Long-Tail Queries Document Re-Ranking on a Search Enginecited by 6
  25. 2024Evaluating Search Engines and Large Language Models for Answering Health Questionscited by 5
  26. 2025Query Understanding in LLM-based Conversational Information Seekingcited by 5
  27. 2025ConvMix: A Mixed-Criteria Data Augmentation Framework for Conversational Dense Retrievalcited by 5
  28. 2025Role-Augmented Intent-Driven Generative Search Engine Optimizationcited by 5
  29. 2024History-Aware Conversational Dense Retrievalcited by 4
  30. 2025ICR: Iterative Clarification and Rewriting for Conversational Searchcited by 4
  31. 2024Engineering Conversational Search Systems: A Review of Applications, Architectures, and Functional Componentscited by 3
  32. 2026Beyond Single-Shot: Multi-step Tool Retrieval via Query Planningcited by 3
  33. 2024Conversational Query Reformulation with the Guidance of Retrieved Documentscited by 2
  34. 2024Enhancing Risk Assessment in Transformers with Loss-at-Risk Functionscited by 2
  35. 2024SRSA: A Cost-Efficient Strategy-Router Search Agent for Real-world Human-Machine Interactionscited by 2
  36. 2025AdaRewriter: Unleashing the Power of Prompting-based Conversational Query Reformulation via Test-Time Adaptationcited by 2
  37. 2025Investigating LLM Variability in Personalized Conversational Information Retrievalcited by 2
  38. 2023Few-Shot Adaptation for Parsing Contextual Utterances with LLMscited by 1

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