Text-to-SQL parsing is an essential and challenging task. The goal of text-to-SQL parsing is
to convert a natural language (NL) question to its corresponding structured query language …

In this paper, we are interested in developing semantic parsers which understand natural
language questions embedded in a conversation with a user and ground them to formal …

Context-dependent text-to-SQL is the task of translating multi-turn questions into database-
related SQL queries. Existing methods typically focus on making full use of history context or …

In this paper, we are interested in developing semantic parsers which understand natural
language questions embedded in a conversation with a user and ground them to formal …

In the information age, semantic parsing technology drives efficiency improvement and
accelerates the process of intelligence. However, it faces complex understanding, data …

We propose a sentence-incremental neural coreference resolution system which
incrementally builds clusters after marking mention boundaries in a shift-reduce method …

Multi-hop question answering from knowledge graphs has gained a growing attention in the
past few years due to its vast applications in AI. Existing approaches in this regard mostly …

We focus on a conversational question answering task which combines the challenges of
understanding questions in context and reasoning over evidence gathered from …

Transliteration is an important task in natural language processing (NLP) which aims to
convert a name in the source language to the target language without changing its …

In this paper we consider the task of conversational semantic parsing over general purpose
knowledge graphs (KGs) with millions of entities, and thousands of relation-types. We focus …