mlsanityData to 7 Oct 2026

Open-Domain Conversational Question Answering with Historical Answers

arXiv 2211.09401 ↗First posted 17 Nov 2022cs.CLcited by 8

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Abstract (arXiv)

Open-domain conversational question answering can be viewed as two tasks: passage retrieval and conversational question answering, where the former relies on selecting candidate passages from a large corpus and the latter requires better understanding of a question with contexts to predict the answers. This paper proposes ConvADR-QA that leverages historical answers to boost retrieval performance and further achieves better answering performance. In our proposed framework, the retrievers use a teacher-student framework to reduce noises from previous turns. Our experiments on the benchmark dataset, OR-QuAC, demonstrate that our model outperforms existing baselines in both extractive and generative reader settings, well justifying the effectiveness of historical answers for open-domain conversational question answering.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 21 of its 25 references that are in the map. First posted on arXiv 17 Nov 2022.

Builds on

21 of 25 references.

References · 21

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  4. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,203
  5. 2020Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrievalcited by 846
  6. 2017Reading Wikipedia to Answer Open-Domain Questionscited by 777
  7. 2018CoQA: A Conversational Question Answering Challengecited by 674
  8. 2018QuAC : Question Answering in Contextcited by 379
  9. 2020Generation-Augmented Retrieval for Open-domain Question Answeringcited by 186
  10. 2018Neural Approaches to Conversational AIcited by 164
  11. 2020Open-Retrieval Conversational Question Answeringcited by 99
  12. 2021TopiOCQA: Open-domain Conversational Question Answering with Topic Switchingcited by 95
9 more
  1. 2021Few-Shot Conversational Dense Retrievalcited by 71
  2. 2019BERT with History Answer Embedding for Conversational Question Answeringcited by 67
  3. 2020TREC CAsT 2019: The Conversational Assistance Track Overviewcited by 64
  4. 2019GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehensioncited by 41
  5. 2018FlowQA: Grasping Flow in History for Conversational Machine Comprehensioncited by 33
  6. 2021Rider: Reader-Guided Passage Reranking for Open-Domain Question Answeringcited by 28
  7. 2019FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehensioncited by 19
  8. 2021A Graph-guided Multi-round Retrieval Method for Conversational Open-domain Question Answeringcited by 7
  9. 2019An Empirical Study of Content Understanding in Conversational Question Answeringcited by 4

Built on by

Cited by year

Citing papers per year: 2023: 2; 2024: 4; 2025: 2.

8 papers.

  1. 2024CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Searchcited by 29
  2. 2024Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Searchcited by 10
  3. 2023CONVERSER: Few-Shot Conversational Dense Retrieval with Synthetic Data Generationcited by 6
  4. 2024History-Aware Conversational Dense Retrievalcited by 4
  5. 2025ConvMix: A Mixed-Criteria Data Augmentation Framework for Conversational Dense Retrievalcited by 4
  6. 2023Phrase Retrieval for Open-Domain Conversational Question Answering with Conversational Dependency Modeling via Contrastive Learningcited by 2
  7. 2024Towards Better Generalization in Open-Domain Question Answering by Mitigating Context Memorizationcited by 0
  8. 2025Adaptive Personalized Conversational Information Retrievalcited by 0