  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.
