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Open-Retrieval Conversational Question Answering

arXiv 2005.11364 ↗First posted 22 May 2020cs.IR cs.CLcited by 99

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Abstract (arXiv)

Conversational search is one of the ultimate goals of information retrieval. Recent research approaches conversational search by simplified settings of response ranking and conversational question answering, where an answer is either selected from a given candidate set or extracted from a given passage. These simplifications neglect the fundamental role of retrieval in conversational search. To address this limitation, we introduce an open-retrieval conversational question answering (ORConvQA) setting, where we learn to retrieve evidence from a large collection before extracting answers, as a further step towards building functional conversational search systems. We create a dataset, OR-QuAC, to facilitate research on ORConvQA. We build an end-to-end system for ORConvQA, featuring a retriever, a reranker, and a reader that are all based on Transformers. Our extensive experiments on OR-QuAC demonstrate that a learnable retriever is crucial for ORConvQA. We further show that our system can make a substantial improvement when we enable history modeling in all system components. Moreover, we show that the reranker component contributes to the model performance by providing a regularization effect. Finally, further in-depth analyses are performed to provide new insights into ORConvQA.

Key facts. Cited by 99 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 May 2020.

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Citing papers per year: 2021: 22; 2022: 15; 2023: 16; 2024: 29; 2025: 14; 2026: 3.

99 papers.

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  1. 2021Large Dual Encoders Are Generalizable Retrieverscited by 454
  2. 2021Retrieving and Reading: A Comprehensive Survey on Open-domain Question Answeringcited by 178
  3. 2021TopiOCQA: Open-domain Conversational Question Answering with Topic Switchingcited by 95
  4. 2024ChatQA: Surpassing GPT-4 on Conversational QA and RAGcited by 90
  5. 2025LocAgent: Graph-Guided LLM Agents for Code Localizationcited by 82
  6. 2021CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learningcited by 68
  7. 2023ConvGQR: Generative Query Reformulation for Conversational Searchcited by 59
  8. 2023Large Language Models are Visual Reasoning Coordinatorscited by 58
  9. 2022Dialog Inpainting: Turning Documents into Dialogscited by 56
  10. 2021MultiDoc2Dial: Modeling Dialogues Grounded in Multiple Documentscited by 53
  11. 2024CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Modelscited by 50
  12. 2025MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systemscited by 50
38 more
  1. 2022Neural Approaches to Conversational Information Retrievalcited by 41
  2. 2021Conversational Question Answering: A Surveycited by 31
  3. 2021Semi-Supervised Variational Reasoning for Medical Dialogue Generationcited by 30
  4. 2024CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Searchcited by 29
  5. 2021Learn to Resolve Conversational Dependency: A Consistency Training Framework for Conversational Question Answeringcited by 27
  6. 2022Conversational Question Answering on Heterogeneous Sourcescited by 26
  7. 2023Learning to Relate to Previous Turns in Conversational Searchcited by 26
  8. 2024Book2Dial: Generating Teacher-Student Interactions from Textbooks for Cost-Effective Development of Educational Chatbotscited by 25
  9. 2023Personalized Large Language Model Assistant with Evolving Conditional Memorycited by 24
  10. 2024Ask Optimal Questions: Aligning Large Language Models with Retriever's Preference in Conversationcited by 23
  11. 2024A Survey of Conversational Searchcited by 22
  12. 2025A Comprehensive Survey on Reinforcement Learning-based Agentic Search: Foundations, Roles, Optimizations, Evaluations, and Applicationscited by 21
  13. 2021Ditch the Gold Standard: Re-evaluating Conversational Question Answeringcited by 19
  14. 2024RAD-Bench: Evaluating Large Language Models Capabilities in Retrieval Augmented Dialoguescited by 19
  15. 2021Reinforcement Learning from Reformulations in Conversational Question Answering over Knowledge Graphscited by 18
  16. 2022Saving Dense Retriever from Shortcut Dependency in Conversational Searchcited by 18
  17. 2021Question Answering Survey: Directions, Challenges, Datasets, Evaluation Matricescited by 17
  18. 2022Generating Information-Seeking Conversations from Unlabeled Documentscited by 17
  19. 2023Query Performance Prediction: From Ad-hoc to Conversational Searchcited by 16
  20. 2024Adaptive Query Rewriting: Aligning Rewriters through Marginal Probability of Conversational Answerscited by 15
  21. 2024AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignmentcited by 14
  22. 2022On the Robustness of Dialogue History Representation in Conversational Question Answering: A Comprehensive Study and a New Prompt-based Methodcited by 12
  23. 2021Open-Retrieval Conversational Machine Readingcited by 11
  24. 2024Retrieval-Enhanced Machine Learning: Synthesis and Opportunitiescited by 11
  25. 2025UniConv: Unifying Retrieval and Response Generation for Large Language Models in Conversationscited by 11
  26. 2023MoqaGPT : Zero-Shot Multi-modal Open-domain Question Answering with Large Language Modelcited by 10
  27. 2024How to Leverage Personal Textual Knowledge for Personalized Conversational Information Retrievalcited by 10
  28. 2024Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Searchcited by 10
  29. 2023Dialogizer: Context-aware Conversational-QA Dataset Generation from Textual Sourcescited by 9
  30. 2022Open-Domain Conversational Question Answering with Historical Answerscited by 8
  31. 2024ConvSDG: Session Data Generation for Conversational Searchcited by 8
  32. 2024DiSCo: LLM Knowledge Distillation for Efficient Sparse Retrieval in Conversational Searchcited by 8
  33. 2024CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation Generationcited by 8
  34. 2025Conversational Search: From Fundamentals to Frontiers in the LLM Eracited by 8
  35. 2025REFRAG: Rethinking RAG based Decodingcited by 8
  36. 2021A Graph-guided Multi-round Retrieval Method for Conversational Open-domain Question Answeringcited by 7
  37. 2021Conversational Machine Reading Comprehension for Vietnamese Healthcare Textscited by 7
  38. 2022P^3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-based Learning and Pre-finetuningcited by 7

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