4 citations · 9 across the 6 of their papers we have counts for
6 papers
Hierarchy-Aware T5 with Path-Adaptive Mask Mechanism for Hierarchical Text Classification
Wei Huang, Chen Liu, Yihua Zhao +4
Hierarchical Text Classification (HTC), which aims to predict text labels organized in hierarchical space, is a significant task lacking in investigation in natural language proces…
FLiText: A Faster and Lighter Semi-Supervised Text Classification with Convolution Networks
Chen Liu, Mengchao Zhang, Zhibin Fu +2
In natural language processing (NLP), state-of-the-art (SOTA) semi-supervised learning (SSL) frameworks have shown great performance on deep pre-trained language models such as BER…
Robust Spoken Language Understanding with RL-based Value Error Recovery
Chen Liu, Su Zhu, Lu Chen +1
Spoken Language Understanding (SLU) aims to extract structured semantic representations (e.g., slot-value pairs) from speech recognized texts, which suffers from errors of Automati…
Unsupervised Dual Paraphrasing for Two-stage Semantic Parsing
Ruisheng Cao, Su Zhu, Chenyu Yang +5
One daunting problem for semantic parsing is the scarcity of annotation. Aiming to reduce nontrivial human labor, we propose a two-stage semantic parsing framework, where the first…
Jointly Encoding Word Confusion Network and Dialogue Context with BERT for Spoken Language Understanding
Chen Liu, Su Zhu, Zijian Zhao +3
Spoken Language Understanding (SLU) converts hypotheses from automatic speech recognizer (ASR) into structured semantic representations. ASR recognition errors can severely degener…
Semantic Parsing with Dual Learning
Ruisheng Cao, Su Zhu, Chen Liu +2
Semantic parsing converts natural language queries into structured logical forms. The paucity of annotated training samples is a fundamental challenge in this field. In this work,…