mlsanityData to 7 Oct 2026

ConvGQR: Generative Query Reformulation for Conversational Search

arXiv 2305.15645 ↗First posted 25 May 2023cs.IR cs.CLcited by 59

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Abstract (arXiv)

In conversational search, the user's real search intent for the current turn is dependent on the previous conversation history. It is challenging to determine a good search query from the whole conversation context. To avoid the expensive re-training of the query encoder, most existing methods try to learn a rewriting model to de-contextualize the current query by mimicking the manual query rewriting. However, manually rewritten queries are not always the best search queries. Training a rewriting model on them would limit the model's ability to produce good search queries. Another useful hint is the potential answer to the question. In this paper, we propose ConvGQR, a new framework to reformulate conversational queries based on generative pre-trained language models (PLMs), one for query rewriting and another for generating potential answers. By combining both, ConvGQR can produce better search queries. In addition, to relate query reformulation to retrieval performance, we propose a knowledge infusion mechanism to optimize both query reformulation and retrieval. Extensive experiments on four conversational search datasets demonstrate the effectiveness of ConvGQR.

Key facts. Cited by 59 papers in the map (data through 7 Oct 2026). Builds on 29 of its 54 references that are in the map. First posted on arXiv 25 May 2023.

Builds on

29 of 54 references.

References · 29

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
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  8. 2020Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrievalcited by 846
  9. 2020How Much Knowledge Can You Pack Into the Parameters of a Language Model?cited by 713
  10. 2018QuAC : Question Answering in Contextcited by 379
  11. 2020Generation-Augmented Retrieval for Open-domain Question Answeringcited by 186
  12. 2020Open-Domain Question Answering Goes Conversational via Question Rewritingcited by 147
17 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. 2021CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learningcited by 68
  8. 2020TREC CAsT 2019: The Conversational Assistance Track Overviewcited by 64
  9. 2020Query Resolution for Conversational Search with Limited Supervisioncited by 52
  10. 2018Pytrec_eval: An Extremely Fast Python Interface to trec_evalcited by 46
  11. 2020Conversational Question Reformulation via Sequence-to-Sequence Architectures and Pretrained Language Modelscited by 45
  12. 2022Neural Approaches to Conversational Information Retrievalcited by 41
  13. 2021Contextualized Query Embeddings for Conversational Searchcited by 36
  14. 2020Guided Transformer: Leveraging Multiple External Sources for Representation Learning in Conversational Searchcited by 23
  15. 2022Saving Dense Retriever from Shortcut Dependency in Conversational Searchcited by 18
  16. 2021A Comparison of Question Rewriting Methods for Conversational Passage Retrievalcited by 16
  17. 2022Enhancing User Behavior Sequence Modeling by Generative Tasks for Session Searchcited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 22; 2025: 17; 2026: 17.

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  1. 2024ChatQA: Surpassing GPT-4 on Conversational QA and RAGcited by 90
  2. 2023Enhancing Conversational Search: Large Language Model-Aided Informative Query Rewritingcited by 69
  3. 2024RaFe: Ranking Feedback Improves Query Rewriting for RAGcited by 47
  4. 2024CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Searchcited by 29
  5. 2025Entropy-based Exploration Conduction for Multi-step Reasoningcited by 28
  6. 2023Learning to Relate to Previous Turns in Conversational Searchcited by 26
  7. 2025Riddle Me This! Stealthy Membership Inference for Retrieval-Augmented Generationcited by 26
  8. 2024Ask Optimal Questions: Aligning Large Language Models with Retriever's Preference in Conversationcited by 23
  9. 2024GenQREnsemble: Zero-Shot LLM Ensemble Prompting for Generative Query Reformulationcited by 22
  10. 2024A Survey of Conversational Searchcited by 22
  11. 2024Conv-CoA: Improving Open-domain Question Answering in Large Language Models via Conversational Chain-of-Actioncited by 19
  12. 2025Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM Collaborationcited by 19
38 more
  1. 2024Query Performance Prediction using Relevance Judgments Generated by Large Language Modelscited by 18
  2. 2024ChatRetriever: Adapting Large Language Models for Generalized and Robust Conversational Dense Retrievalcited by 18
  3. 2024Generalizing Conversational Dense Retrieval via LLM-Cognition Data Augmentationcited by 16
  4. 2024AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignmentcited by 14
  5. 2025UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversationscited by 11
  6. 2026OpenDecoder: Open Large Language Model Decoding to Incorporate Document Quality in RAGcited by 11
  7. 2024How to Leverage Personal Textual Knowledge for Personalized Conversational Information Retrievalcited by 10
  8. 2024Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Searchcited by 10
  9. 2024MaFeRw: Query Rewriting with Multi-Aspect Feedbacks for Retrieval-Augmented Large Language Modelscited by 9
  10. 2024Learning When to Retrieve, What to Rewrite, and How to Respond in Conversational QAcited by 9
  11. 2024ConvSDG: Session Data Generation for Conversational Searchcited by 8
  12. 2024DiSCo: LLM Knowledge Distillation for Efficient Sparse Retrieval in Conversational Searchcited by 8
  13. 2025Conversational Search: From Fundamentals to Frontiers in the LLM Eracited by 8
  14. 2023Robust Training for Conversational Question Answering Models with Reinforced Reformulation Generationcited by 7
  15. 2025ReVision: A Dataset and Baseline VLM for Privacy-Preserving Task-Oriented Visual Instruction Rewritingcited by 6
  16. 2025Can Pre-training Indicators Reliably Predict Fine-tuning Outcomes of LLMs?cited by 6
  17. 2024Generative Query Reformulation Using Ensemble Prompting, Document Fusion, and Relevance Feedbackcited by 5
  18. 2025CRMWeaver: Building Powerful Business Agent via Agentic RL and Shared Memoriescited by 5
  19. 2026ReAttn: Improving Attention-based Re-ranking via Attention Re-weightingcited by 5
  20. 2024History-Aware Conversational Dense Retrievalcited by 4
  21. 2025Query Understanding in LLM-based Conversational Information Seekingcited by 4
  22. 2025ConvMix: A Mixed-Criteria Data Augmentation Framework for Conversational Dense Retrievalcited by 4
  23. 2025ICR: Iterative Clarification and Rewriting for Conversational Searchcited by 4
  24. 2026Connect the Dots: Knowledge Graph-Guided Crawler Attack on Retrieval-Augmented Generation Systemscited by 3
  25. 2024Conversational Query Reformulation with the Guidance of Retrieved Documentscited by 2
  26. 2024Enhancing Risk Assessment in Transformers with Loss-at-Risk Functionscited by 2
  27. 2025AdaRewriter: Unleashing the Power of Prompting-based Conversational Query Reformulation via Test-Time Adaptationcited by 2
  28. 2026A Reproducibility Study of LLM-Based Query Reformulationcited by 2
  29. 2026Training LLMs with Reinforcement Learning for Intent-Aware Personalized Question Answeringcited by 2
  30. 2025Test-Time Scaling Strategies for Generative Retrieval in Multimodal Conversational Recommendationscited by 1
  31. 2026Multi-Faceted Self-Consistent Preference Alignment for Query Rewriting in Conversational Searchcited by 1
  32. 2026QueryAgent-R1: Bridging Query Generation and Product Retrieval for E-Commerce Query Recommendationcited by 1
  33. 2024Iterative NLP Query Refinement for Enhancing Domain-Specific Information Retrieval: A Case Study in Career Servicescited by 0
  34. 2025References Indeed Matter? Reference-Free Preference Optimization for Conversational Query Reformulationcited by 0
  35. 2025WXImpactBench: A Disruptive Weather Impact Understanding Benchmark for Evaluating Large Language Modelscited by 0
  36. 2025Building Open-Retrieval Conversational Question Answering Systems by Generating Synthetic Data and Decontextualizing User Questionscited by 0
  37. 2025Can Synthetic Query Rewrites Capture User Intent Better than Humans in Retrieval-Augmented Generation?cited by 0
  38. 2026Evaluating the Utility of Grounding Documents with Reference-Free LLM-based Metricscited by 0

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