A Survey on Table Question Answering: Recent Advances
July 12, 2022 ยท The Cartographer ยท ๐ China Conference on Knowledge Graph and Semantic Computing
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"Title-pattern auto-detect: A Survey on Table Question Answering: Recent Advances"
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Authors
Nengzheng Jin, Joanna Siebert, Dongfang Li, Qingcai Chen
arXiv ID
2207.05270
Category
cs.CL: Computation & Language
Cross-listed
cs.AI
Citations
71
Venue
China Conference on Knowledge Graph and Semantic Computing
Last Checked
23 hours ago
Abstract
Table Question Answering (Table QA) refers to providing precise answers from tables to answer a user's question. In recent years, there have been a lot of works on table QA, but there is a lack of comprehensive surveys on this research topic. Hence, we aim to provide an overview of available datasets and representative methods in table QA. We classify existing methods for table QA into five categories according to their techniques, which include semantic-parsing-based, generative, extractive, matching-based, and retriever-reader-based methods. Moreover, as table QA is still a challenging task for existing methods, we also identify and outline several key challenges and discuss the potential future directions of table QA.
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