mlsanityData to 14 Oct 2026

Conversational Search: From Fundamentals to Frontiers in the LLM Era

arXiv 2506.10635 ↗First posted 12 Jun 2025cs.IR cs.CLcited by 8

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Abstract (arXiv)

Conversational search enables multi-turn interactions between users and systems to fulfill users' complex information needs. During this interaction, the system should understand the users' search intent within the conversational context and then return the relevant information through a flexible, dialogue-based interface. The recent powerful large language models (LLMs) with capacities of instruction following, content generation, and reasoning, attract significant attention and advancements, providing new opportunities and challenges for building up intelligent conversational search systems. This tutorial aims to introduce the connection between fundamentals and the emerging topics revolutionized by LLMs in the context of conversational search. It is designed for students, researchers, and practitioners from both academia and industry. Participants will gain a comprehensive understanding of both the core principles and cutting-edge developments driven by LLMs in conversational search, equipping them with the knowledge needed to contribute to the development of next-generation conversational search systems.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 36 of its 69 references that are in the map. First posted on arXiv 12 Jun 2025.

Builds on

36 of 69 references.

References · 36

  1. 2025Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learningcited by 1,444
  2. 2025Search-o1: Agentic Search-Enhanced Large Reasoning Modelscited by 433
  3. 2023Large Language Models for Information Retrieval: A Surveycited by 331
  4. 2020Open-Domain Question Answering Goes Conversational via Question Rewritingcited by 148
  5. 2019Asking Clarifying Questions in Open-Domain Information-Seeking Conversationscited by 139
  6. 2020Open-Retrieval Conversational Question Answeringcited by 99
  7. 2021TopiOCQA: Open-domain Conversational Question Answering with Topic Switchingcited by 96
  8. 2020Few-Shot Generative Conversational Query Rewritingcited by 85
  9. 2023Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Searchcited by 75
  10. 2021Few-Shot Conversational Dense Retrievalcited by 72
  11. 2021CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learningcited by 68
  12. 2021Building and Evaluating Open-Domain Dialogue Corpora with Clarifying Questionscited by 63
24 more
  1. 2024DRAGIN: Dynamic Retrieval Augmented Generation based on the Information Needs of Large Language Modelscited by 63
  2. 2023ConvGQR: Generative Query Reformulation for Conversational Searchcited by 59
  3. 2020Query Resolution for Conversational Search with Limited Supervisioncited by 52
  4. 2025MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systemscited by 51
  5. 2024Towards Human-centered Proactive Conversational Agentscited by 49
  6. 2022Neural Approaches to Conversational Information Retrievalcited by 42
  7. 2021Contextualized Query Embeddings for Conversational Searchcited by 37
  8. 2022Conversational Information Seekingcited by 37
  9. 2024USimAgent: Large Language Models for Simulating Search Userscited by 32
  10. 2024CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Searchcited by 29
  11. 2023Learning to Relate to Previous Turns in Conversational Searchcited by 26
  12. 2024Ranked List Truncation for Large Language Model-based Re-Rankingcited by 20
  13. 2024TREC iKAT 2023: A Test Collection for Evaluating Conversational and Interactive Knowledge Assistantscited by 17
  14. 2024Can We Use Large Language Models to Fill Relevance Judgment Holes?cited by 17
  15. 2021A Comparison of Question Rewriting Methods for Conversational Passage Retrievalcited by 16
  16. 2023Query Performance Prediction: From Ad-hoc to Conversational Searchcited by 16
  17. 2024How to Leverage Personal Textual Knowledge for Personalized Conversational Information Retrievalcited by 11
  18. 2024Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Searchcited by 11
  19. 2024ConvSDG: Session Data Generation for Conversational Searchcited by 8
  20. 2025Conversational Gold: Evaluating Personalized Conversational Search System using Gold Nuggetscited by 8
  21. 2025Zero-Shot and Efficient Clarification Need Prediction in Conversational Searchcited by 4
  22. 2024Generative Retrieval with Few-shot Indexingcited by 3
  23. 2025Do Retrieval-Augmented Language Models Adapt to Varying User Needs?cited by 2
  24. 2025Improving the Reusability of Conversational Search Test Collectionscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 6; 2026: 2.

8 papers.

  1. 2025UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversationscited by 12
  2. 2025LocalSearchBench: Benchmarking Agentic Search in Real-World Local Life Servicescited by 8
  3. 2025ConvMix: A Mixed-Criteria Data Augmentation Framework for Conversational Dense Retrievalcited by 5
  4. 2026Diagnosing and Repairing Citation Failures in Generative Engine Optimizationcited by 3
  5. 2025Adaptive Personalized Conversational Information Retrievalcited by 1
  6. 2025From Deferral to Learning: Online In-Context Knowledge Distillation for LLM Cascadescited by 1
  7. 2025MEASER: Malware embedding attacks on open-source LLMscited by 0
  8. 2026Re-Rankers as Relevance Judgescited by 0