mlsanityData to 7 Oct 2026

CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Search

arXiv 2406.05013 ↗First posted 7 Jun 2024cs.IR cs.CLcited by 29

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Abstract (arXiv)

In this paper, we study how open-source large language models (LLMs) can be effectively deployed for improving query rewriting in conversational search, especially for ambiguous queries. We introduce CHIQ, a two-step method that leverages the capabilities of LLMs to resolve ambiguities in the conversation history before query rewriting. This approach contrasts with prior studies that predominantly use closed-source LLMs to directly generate search queries from conversation history. We demonstrate on five well-established benchmarks that CHIQ leads to state-of-the-art results across most settings, showing highly competitive performances with systems leveraging closed-source LLMs. Our study provides a first step towards leveraging open-source LLMs in conversational search, as a competitive alternative to the prevailing reliance on commercial LLMs. Data, models, and source code will be publicly available upon acceptance at https://github.com/fengranMark/CHIQ.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). Builds on 35 of its 57 references that are in the map. First posted on arXiv 7 Jun 2024.

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35 of 57 references.

References · 35

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  10. 2023The False Promise of Imitating Proprietary LLMscited by 254
  11. 2022BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagecited by 197
  12. 2020Open-Domain Question Answering Goes Conversational via Question Rewritingcited by 147
23 more
  1. 2020Open-Retrieval Conversational Question Answeringcited by 99
  2. 2021TopiOCQA: Open-domain Conversational Question Answering with Topic Switchingcited by 95
  3. 2020Question Rewriting for Conversational Question Answeringcited by 93
  4. 2020Few-Shot Generative Conversational Query Rewritingcited by 85
  5. 2023Large Language Models Know Your Contextual Search Intent: A Prompting Framework for Conversational Searchcited by 74
  6. 2021Few-Shot Conversational Dense Retrievalcited by 71
  7. 2023Enhancing Conversational Search: Large Language Model-Aided Informative Query Rewritingcited by 69
  8. 2021CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learningcited by 68
  9. 2020TREC CAsT 2019: The Conversational Assistance Track Overviewcited by 64
  10. 2023ConvGQR: Generative Query Reformulation for Conversational Searchcited by 59
  11. 2022Dialog Inpainting: Turning Documents into Dialogscited by 56
  12. 2020Query Resolution for Conversational Search with Limited Supervisioncited by 52
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  14. 2020Conversational Question Reformulation via Sequence-to-Sequence Architectures and Pretrained Language Modelscited by 45
  15. 2022Neural Approaches to Conversational Information Retrievalcited by 41
  16. 2021Contextualized Query Embeddings for Conversational Searchcited by 36
  17. 2023Learning to Relate to Previous Turns in Conversational Searchcited by 26
  18. 2024Ask Optimal Questions: Aligning Large Language Models with Retriever's Preference in Conversationcited by 23
  19. 2022Saving Dense Retriever from Shortcut Dependency in Conversational Searchcited by 18
  20. 2024ChatRetriever: Adapting Large Language Models for Generalized and Robust Conversational Dense Retrievalcited by 18
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 8; 2025: 14; 2026: 7.

29 papers.

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  1. 2025A Survey of Personalization: From RAG to Agentcited by 26
  2. 2024A Survey of Conversational Searchcited by 22
  3. 2024AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignmentcited by 14
  4. 2025UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversationscited by 11
  5. 2024How to Leverage Personal Textual Knowledge for Personalized Conversational Information Retrievalcited by 10
  6. 2024Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Searchcited by 10
  7. 2024DiSCo: LLM Knowledge Distillation for Efficient Sparse Retrieval in Conversational Searchcited by 8
  8. 2025Conversational Gold: Evaluating Personalized Conversational Search System using Gold Nuggetscited by 8
  9. 2025Conversational Search: From Fundamentals to Frontiers in the LLM Eracited by 8
  10. 2025RECAP: REwriting Conversations for Intent Understanding in Agentic Planningcited by 7
  11. 2025ConvMix: A Mixed-Criteria Data Augmentation Framework for Conversational Dense Retrievalcited by 4
  12. 2025ICR: Iterative Clarification and Rewriting for Conversational Searchcited by 4
17 more
  1. 2024IRLab@iKAT24: Learned Sparse Retrieval with Multi-aspect LLM Query Generation for Conversational Searchcited by 3
  2. 2025MAPS: Motivation-Aware Personalized Search via LLM-Driven Consultation Alignmentcited by 3
  3. 2024Conversational Query Reformulation with the Guidance of Retrieved Documentscited by 2
  4. 2025AdaRewriter: Unleashing the Power of Prompting-based Conversational Query Reformulation via Test-Time Adaptationcited by 2
  5. 2025Investigating LLM Variability in Personalized Conversational Information Retrievalcited by 2
  6. 2024A Survey of Query Optimization in Large Language Modelscited by 1
  7. 2026Multi-Faceted Self-Consistent Preference Alignment for Query Rewriting in Conversational Searchcited by 1
  8. 2025WXImpactBench: A Disruptive Weather Impact Understanding Benchmark for Evaluating Large Language Modelscited by 0
  9. 2025Adaptive Personalized Conversational Information Retrievalcited by 0
  10. 2025CFDA & CLIP at TREC iKAT 2025: Enhancing Personalized Conversational Search via Query Reformulation and Rank Fusioncited by 0
  11. 2025Can Synthetic Query Rewrites Capture User Intent Better than Humans in Retrieval-Augmented Generation?cited by 0
  12. 2026When should I search more: Adaptive Complex Query Optimization with Reinforcement Learningcited by 0
  13. 2026RCEM: Robust Conversational Search EMbedder in Distributional Shiftcited by 0
  14. 2026uva-irlab-conv at SemEval-2026 Task 8: Multi-Turn RAG with Learned Sparse Retrieval and Listwise Rerankingcited by 0
  15. 2026Preference Shapes Relevance: Cross-component Hierarchical Semantic Alignment for Personalized Generative Retrievalcited by 0
  16. 2026CompCQR: Compositional Query Generation for Training-Free Conversational Searchcited by 0
  17. 2026Lost in Conversation or Lost in Translation? Diagnosing Multi-Turn Degradation in RAGcited by 0