9 citations · 16 across the 5 of their papers we have counts for
5 papers
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…
HeteroQA: Learning towards Question-and-Answering through Multiple Information Sources via Heterogeneous Graph Modeling
Shen Gao, Yuchi Zhang, Yongliang Wang +4
Community Question Answering (CQA) is a well-defined task that can be used in many scenarios, such as E-Commerce and online user community for special interests. In these communiti…
S+PAGE: A Speaker and Position-Aware Graph Neural Network Model for Emotion Recognition in Conversation
Chen Liang, Chong Yang, Jing Xu +3
Emotion recognition in conversation (ERC) has attracted much attention in recent years for its necessity in widespread applications. Existing ERC methods mostly model the self and…
Relation Aware Semi-autoregressive Semantic Parsing for NL2SQL
Junyang Huang, Yongbo Wang, Yongliang Wang +2
Natural language to SQL (NL2SQL) aims to parse a natural language with a given database into a SQL query, which widely appears in practical Internet applications. Jointly encode da…
SeaD: End-to-end Text-to-SQL Generation with Schema-aware Denoising
Kuan Xu, Yongbo Wang, Yongliang Wang +2
In text-to-SQL task, seq-to-seq models often lead to sub-optimal performance due to limitations in their architecture. In this paper, we present a simple yet effective approach tha…