mlsanityData to 7 Oct 2026

AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignment

arXiv 2407.01965 ↗First posted 2 Jul 2024cs.CL cs.IRcited by 14

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Abstract (arXiv)

Conversational Query Reformulation (CQR) has significantly advanced in addressing the challenges of conversational search, particularly those stemming from the latent user intent and the need for historical context. Recent works aimed to boost the performance of CQR through alignment. However, they are designed for one specific retrieval system, which potentially results in sub-optimal generalization. To overcome this limitation, we present a novel framework AdaCQR. By aligning reformulation models with both term-based and semantic-based retrieval systems, AdaCQR enhances the generalizability of information-seeking queries among diverse retrieval environments through a two-stage training strategy. Moreover, two effective approaches are proposed to obtain superior labels and diverse input candidates, boosting the efficiency and robustness of the framework. Experimental results on the TopiOCQA and QReCC datasets demonstrate that AdaCQR outperforms the existing methods in a more efficient framework, offering both quantitative and qualitative improvements in conversational query reformulation.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 38 of its 55 references that are in the map. First posted on arXiv 2 Jul 2024.

Builds on

38 of 55 references.

References · 38

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26 more
  1. 2020Sparse, Dense, and Attentional Representations for Text Retrievalcited by 213
  2. 2022BRIO: Bringing Order to Abstractive Summarizationcited by 161
  3. 2020Open-Domain Question Answering Goes Conversational via Question Rewritingcited by 147
  4. 2023Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoningcited by 140
  5. 2020Open-Retrieval Conversational Question Answeringcited by 99
  6. 2021TopiOCQA: Open-domain Conversational Question Answering with Topic Switchingcited by 95
  7. 2020Question Rewriting for Conversational Question Answeringcited by 93
  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 74
  10. 2021Few-Shot Conversational Dense Retrievalcited by 71
  11. 2023Enhancing Conversational Search: Large Language Model-Aided Informative Query Rewritingcited by 69
  12. 2021CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learningcited by 68
  13. 2023ConvGQR: Generative Query Reformulation for Conversational Searchcited by 59
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 7; 2026: 7.

14 papers.

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  1. 2025UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversationscited by 11
  2. 2025CRMWeaver: Building Powerful Business Agent via Agentic RL and Shared Memoriescited by 5
  3. 2025ConvMix: A Mixed-Criteria Data Augmentation Framework for Conversational Dense Retrievalcited by 4
  4. 2025ICR: Iterative Clarification and Rewriting for Conversational Searchcited by 4
  5. 2025AdaRewriter: Unleashing the Power of Prompting-based Conversational Query Reformulation via Test-Time Adaptationcited by 2
  6. 2026ReFormeR: Learning and Applying Explicit Query Reformulation Patternscited by 1
  7. 2026Multi-Faceted Self-Consistent Preference Alignment for Query Rewriting in Conversational Searchcited by 1
  8. 2025References Indeed Matter? Reference-Free Preference Optimization for Conversational Query Reformulationcited by 0
  9. 2025Can Synthetic Query Rewrites Capture User Intent Better than Humans in Retrieval-Augmented Generation?cited by 0
  10. 2026When should I search more: Adaptive Complex Query Optimization with Reinforcement Learningcited by 0
  11. 2026Evaluating the Utility of Grounding Documents with Reference-Free LLM-based Metricscited by 0
  12. 2026Beyond Continuity: Challenges of Context Switching in Multi-Turn Dialogue with LLMscited by 0
2 more
  1. 2026RCEM: Robust Conversational Search EMbedder in Distributional Shiftcited by 0
  2. 2026CompCQR: Compositional Query Generation for Training-Free Conversational Searchcited by 0