论文标题
关于桌面问题的调查回答：最新进展
A Survey on Table Question Answering: Recent Advances
论文作者
论文摘要
表问题回答（表QA）是指从表中提供精确的答案来回答用户的问题。近年来，在表质量检查方面有很多作品，但是对该研究主题缺乏全面的调查。因此，我们旨在提供表QA中可用数据集和代表性方法的概述。我们根据其技术将现有的表质量质量质量检查分为五个类别，其中包括基于语义的，生成，提取性，基于匹配的基于匹配的方法和基于检索器阅读器的方法。此外，由于表质量质量检查仍然是现有方法的一项艰巨的任务，因此我们还识别和概述了几个关键挑战，并讨论了表QA的潜在未来方向。
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.
