28 citations · 74 across the 11 of their papers we have counts for
13 papers
STAR: SQL Guided Pre-Training for Context-dependent Text-to-SQL Parsing
Zefeng Cai, Xiangyu Li, Binyuan Hui +8
In this paper, we propose a novel SQL guided pre-training framework STAR for context-dependent text-to-SQL parsing, which leverages contextual information to enrich natural languag…
SUN: Exploring Intrinsic Uncertainties in Text-to-SQL Parsers
Bowen Qin, Lihan Wang, Binyuan Hui +7
This paper aims to improve the performance of text-to-SQL parsing by exploring the intrinsic uncertainties in the neural network based approaches (called SUN). From the data uncert…
Towards Generalizable and Robust Text-to-SQL Parsing
Chang Gao, Bowen Li, Wenxuan Zhang +5
Text-to-SQL parsing tackles the problem of mapping natural language questions to executable SQL queries. In practice, text-to-SQL parsers often encounter various challenging scenar…
SPACE-3: Unified Dialog Model Pre-training for Task-Oriented Dialog Understanding and Generation
Wanwei He, Yinpei Dai, Min Yang +4
Recently, pre-training methods have shown remarkable success in task-oriented dialog (TOD) systems. However, most existing pre-trained models for TOD focus on either dialog underst…
SPACE-2: Tree-Structured Semi-Supervised Contrastive Pre-training for Task-Oriented Dialog Understanding
Wanwei He, Yinpei Dai, Binyuan Hui +6
Pre-training methods with contrastive learning objectives have shown remarkable success in dialog understanding tasks. However, current contrastive learning solely considers the se…
Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting
Mingyang Chen, Wen Zhang, Zhen Yao +4
We study the knowledge extrapolation problem to embed new components (i.e., entities and relations) that come with emerging knowledge graphs (KGs) in the federated setting. In this…