Open-Domain Conversational Question Answering with Historical Answers (2022.findings-aacl)
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| Challenge: | Existing approaches to conversational question answering are limited due to the large number of candidate documents. |
| Approach: | They propose a model that leverages historical answers to boost retrieval performance . they propose to use open-domain conversational question answering to solve these problems . |
| Outcome: | The proposed model outperforms baseline models in extractive and generative reader settings on OR-QuAC dataset. |
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Raviteja Anantha, Svitlana Vakulenko, Zhucheng Tu, Shayne Longpre, Stephen Pulman, Srinivas Chappidi
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Open-Domain Question Answering (2020.acl-tutorials)
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| Challenge: | tutorial provides a comprehensive overview of cutting-edge research in open-domain question answering (QA) |
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| Challenge: | Recent work on open-domain question answering focuses on either extractive or generative readers exclusively. |
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Phrase Retrieval for Open Domain Conversational Question Answering with Conversational Dependency Modeling via Contrastive Learning (2023.findings-acl)
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| Challenge: | Open-Domain Conversational Question Answering (ODConvQA) aims to answer questions through a multi-turn conversation . however, such a pipeline approach makes the reader vulnerable to errors propagated from the retriever, which makes it slower since they are not runnable in parallel. |
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| Challenge: | Existing studies have studied history-dependent reasoning for question answering . utilizing global conversation history for enhancement is gaining interest . |
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Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering (2021.eacl-main)
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| Challenge: | Existing approaches to extracting answer from text are expensive to train and train. |
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Open Domain Question Answering over Tables via Dense Retrieval (2021.naacl-main)
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| Challenge: | Recent advances in open-domain QA focus on retrieving textual passages . a retriever designed to handle tabular context can improve retrieval quality . |
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When to Read Documents or QA History: On Unified and Selective Open-domain QA (2023.findings-acl)
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| Challenge: | Existing work aims to answer factoid questions from an open set of domains using knowledge sources. |
| Approach: | They propose to use QA-pair and document corpora to answer open-domain questions . they propose to apply natural follow-up to both models to find answers . |
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Augmenting Pre-trained Language Models with QA-Memory for Open-Domain Question Answering (2023.eacl-main)
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| Challenge: | Existing methods for open-domain question-answering use an open book approach . a recent alternative is to retrieve from a collection of previously-generated question-annwer pairs . |
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Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study (2021.tacl-1)
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| Challenge: | Recent advances in open-domain question answering (ODQA) have led to human-level performance on many datasets. |
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