Emerging research in Neural Question Generation (NQG) has started to integrate a larger
variety of inputs, and generating questions requiring higher levels of cognition. These trends …

To bridge the gap between users and data, numerous text-to-SQL systems have been
developed that allow users to pose natural language questions over relational databases …

Question answering has emerged as an intuitive way of querying structured data sources
and has attracted significant advancements over the years. A large body of recent work on …

Most recently, there has been significant interest in learning contextual representations for
various NLP tasks, by leveraging large scale text corpora to train powerful language models …

Natural language to SQL (NL2SQL) techniques provide a convenient interface to access
databases, especially for non-expert users, to conduct various data analytics. Existing …

Question answering has emerged as an intuitive way of querying structured data sources,
and has attracted significant advancements over the years. In this article, we provide an …

We focus on the cross-domain context-dependent text-to-SQL generation task. Based on the
observation that adjacent natural language questions are often linguistically dependent and …

Large language models (LLMs) with in-context learning have demonstrated impressive
generalization capabilities in the cross-domain text-to-SQL task, without the use of in …

The ability to ask clarification questions is essential for knowledge-based question
answering (KBQA) systems, especially for handling ambiguous phenomena. Despite its …

This paper investigates a new task named Conversational Question Generation (CQG)
which is to generate a question based on a passage and a conversation history (ie, previous …