mlsanityData to 7 Oct 2026

Neural Approaches to Conversational Information Retrieval

arXiv 2201.05176 ↗First posted 13 Jan 2022cs.IR cs.CLcited by 41

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Abstract (arXiv)

A conversational information retrieval (CIR) system is an information retrieval (IR) system with a conversational interface which allows users to interact with the system to seek information via multi-turn conversations of natural language, in spoken or written form. Recent progress in deep learning has brought tremendous improvements in natural language processing (NLP) and conversational AI, leading to a plethora of commercial conversational services that allow naturally spoken and typed interaction, increasing the need for more human-centric interactions in IR. As a result, we have witnessed a resurgent interest in developing modern CIR systems in both research communities and industry. This book surveys recent advances in CIR, focusing on neural approaches that have been developed in the last few years. This book is based on the authors' tutorial at SIGIR'2020 (Gao et al., 2020b), with IR and NLP communities as the primary target audience. However, audiences with other background, such as machine learning and human-computer interaction, will also find it an accessible introduction to CIR. We hope that this book will prove a valuable resource for students, researchers, and software developers. This manuscript is a working draft. Comments are welcome.

Key facts. Cited by 41 papers in the map (data through 7 Oct 2026). Builds on 123 of its 358 references that are in the map. First posted on arXiv 13 Jan 2022.

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123 of 358 references.

References · 123

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38 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 9; 2023: 12; 2024: 12; 2025: 4; 2026: 4.

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  1. 2023Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedbackcited by 351
  2. 2024Agent AI: Surveying the Horizons of Multimodal Interactioncited by 167
  3. 2022Vision-Language Pre-training: Basics, Recent Advances, and Future Trendscited by 117
  4. 2023Leveraging Large Language Models in Conversational Recommender Systemscited by 63
  5. 2023ConvGQR: Generative Query Reformulation for Conversational Searchcited by 59
  6. 2022GODEL: Large-Scale Pre-Training for Goal-Directed Dialogcited by 50
  7. 2022Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarizationcited by 29
  8. 2024CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Searchcited by 29
  9. 2023Learning to Relate to Previous Turns in Conversational Searchcited by 26
  10. 2023Chatting Makes Perfect: Chat-based Image Retrievalcited by 25
  11. 2024A Survey of Conversational Searchcited by 22
  12. 2022METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signalscited by 20
29 more
  1. 2024ChatRetriever: Adapting Large Language Models for Generalized and Robust Conversational Dense Retrievalcited by 18
  2. 2024STYLE: Improving Domain Transferability of Asking Clarification Questions in Large Language Model Powered Conversational Agentscited by 17
  3. 2022ConTextual Masked Auto-Encoder for Dense Passage Retrievalcited by 16
  4. 2023Zero-shot Clarifying Question Generation for Conversational Searchcited by 14
  5. 2023Advancing the Search Frontier with AI Agentscited by 12
  6. 2023Augmenting Black-box LLMs with Medical Textbooks for Biomedical Question Answeringcited by 11
  7. 2025UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversationscited by 11
  8. 2024Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Searchcited by 10
  9. 2022Query-as-context Pre-training for Dense Passage Retrievalcited by 9
  10. 2024ConvSDG: Session Data Generation for Conversational Searchcited by 8
  11. 2025Conversational Search: From Fundamentals to Frontiers in the LLM Eracited by 8
  12. 2022OPERA: Harmonizing Task-Oriented Dialogs and Information Seeking Experiencecited by 5
  13. 2023CoT-MAE v2: Contextual Masked Auto-Encoder with Multi-view Modeling for Passage Retrievalcited by 5
  14. 2023Construction contract risk identification based on knowledge-augmented language modelcited by 5
  15. 2024History-Aware Conversational Dense Retrievalcited by 4
  16. 2025ConvMix: A Mixed-Criteria Data Augmentation Framework for Conversational Dense Retrievalcited by 4
  17. 2023Interactive Text Generationcited by 2
  18. 2024Position Paper: Agent AI Towards a Holistic Intelligencecited by 2
  19. 2024Conversational Query Reformulation with the Guidance of Retrieved Documentscited by 2
  20. 2023What Types of Questions Require Conversation to Answer? A Case Study of AskReddit Questionscited by 1
  21. 2024Scalable Frame-based Construction of Sociocultural NormBases for Socially-Aware Dialoguescited by 1
  22. 2026Agentic Conversational Search with Contextualized Reasoning via Reinforcement Learningcited by 1
  23. 2026The P-Completeness of Inverted Index Traversal: On the Complexity of Evaluating Boolean Query DAGscited by 1
  24. 2022Sparse and Dense Approaches for the Full-rank Retrieval of Responses for Dialoguescited by 0
  25. 2022Document-Level Abstractive Summarizationcited by 0
  26. 2024Rewriting Conversational Utterances with Instructed Large Language Modelscited by 0
  27. 2025Adaptive Personalized Conversational Information Retrievalcited by 0
  28. 2026Orcheo: A Modular Full-Stack Platform for Conversational Searchcited by 0
  29. 2026Improving Ad-hoc Search Effectiveness for Conversational Information Retrieval via Model Mergingcited by 0