Conversational systems have come a long way since their inception in the 1960s. After
decades of research and development, we have seen progress from Eliza and Parry in the …

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 …

Text-to-SQL parsing, which aims at converting natural language instructions into executable
SQLs, has gained increasing attention in recent years. In particular, GPT-4 and Claude-2 …

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 …

Deep learning has become the dominant approach in addressing various tasks in Natural
Language Processing (NLP). Although text inputs are typically represented as a sequence …

We present Spider, a large-scale, complex and cross-domain semantic parsing and text-to-
SQL dataset annotated by 11 college students. It consists of 10,181 questions and 5,693 …

We present QuAC, a dataset for Question Answering in Context that contains 14K
information-seeking QA dialogs (100K questions in total). The dialogs involve two crowd …

In this work we systematically review the recent advancements in software engineering with
language models, covering 70+ models, 40+ evaluation tasks, 180+ datasets, and 900 …

Spoken Language Understanding infers semantic meaning directly from audio data, and
thus promises to reduce error propagation and misunderstandings in end-user applications …

We present BRIDGE, a powerful sequential architecture for modeling dependencies
between natural language questions and relational databases in cross-DB semantic …