118 citations · 179 across the 13 of their papers we have counts for
12 papers · 1 filter
Learn from Yesterday: A Semi-Supervised Continual Learning Method for Supervision-Limited Text-to-SQL Task Streams
Yongrui Chen, Xinnan Guo, Tongtong Wu +3
Conventional text-to-SQL studies are limited to a single task with a fixed-size training and test set. When confronted with a stream of tasks common in real-world applications, exi…
Towards Relation Extraction From Speech
Tongtong Wu, Guitao Wang, Jinming Zhao +4
Relation extraction typically aims to extract semantic relationships between entities from the unstructured text. One of the most essential data sources for relation extraction is…
Neural Topic Modeling with Deep Mutual Information Estimation
Kang Xu, Xiaoqiu Lu, Yuan-fang Li +5
The emerging neural topic models make topic modeling more easily adaptable and extendable in unsupervised text mining. However, the existing neural topic models is difficult to ret…
Simple or Complex? Complexity-Controllable Question Generation with Soft Templates and Deep Mixture of Experts Model
Sheng Bi, Xiya Cheng, Yuan-Fang Li +5
The ability to generate natural-language questions with controlled complexity levels is highly desirable as it further expands the applicability of question generation. In this pap…
Leveraging Table Content for Zero-shot Text-to-SQL with Meta-Learning
Yongrui Chen, Xinnan Guo, Chaojie Wang +4
Single-table text-to-SQL aims to transform a natural language question into a SQL query according to one single table. Recent work has made promising progress on this task by pre-t…
Formal Query Building with Query Structure Prediction for Complex Question Answering over Knowledge Base
Yongrui Chen, Huiying Li, Yuncheng Hua +1
Formal query building is an important part of complex question answering over knowledge bases. It aims to build correct executable queries for questions. Recent methods try to rank…