activity
20182021
most citedPrefix-to-SQL: Text-to-SQL Generation from Incomplete User Questions

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CL20211 cited

Prefix-to-SQL: Text-to-SQL Generation from Incomplete User Questions

Naihao Deng, Shuaichen Chang, Peng Shi +2

Existing text-to-SQL research only considers complete questions as the input, but lay-users might strive to formulate a complete question. To build a smarter natural language inter…

cs.CL2021

ExplainaBoard: An Explainable Leaderboard for NLP

Pengfei Liu, Jinlan Fu, Yang Xiao +7

With the rapid development of NLP research, leaderboards have emerged as one tool to track the performance of various systems on various NLP tasks. They are effective in this goal…

cs.CL2020

Did You Ask a Good Question? A Cross-Domain Question Intention Classification Benchmark for Text-to-SQL

Yusen Zhang, Xiangyu Dong, Shuaichen Chang +3

Neural models have achieved significant results on the text-to-SQL task, in which most current work assumes all the input questions are legal and generates a SQL query for any inpu…

cs.CL2019

Zero-shot Text-to-SQL Learning with Auxiliary Task

Shuaichen Chang, Pengfei Liu, Yun Tang +3

Recent years have seen great success in the use of neural seq2seq models on the text-to-SQL task. However, little work has paid attention to how these models generalize to realisti…

cs.CL2018

Contextualized Non-local Neural Networks for Sequence Learning

Pengfei Liu, Shuaichen Chang, Xuanjing Huang +2

Recently, a large number of neural mechanisms and models have been proposed for sequence learning, of which self-attention, as exemplified by the Transformer model, and graph neura…