23 citations · 36 across the 8 of their papers we have counts for
8 papers
Constrained Multi-Layer Contrastive Learning for Implicit Discourse Relationship Recognition
Yiheng Wu, Junhui Li, Muhua Zhu
Previous approaches to the task of implicit discourse relation recognition (IDRR) generally view it as a classification task. Even with pre-trained language models, like BERT and R…
Exploiting Rich Syntax for Better Knowledge Base Question Answering
Pengju Zhang, Yonghui Jia, Muhua Zhu +2
Recent studies on Knowledge Base Question Answering (KBQA) have shown great progress on this task via better question understanding. Previous works for encoding questions mainly fo…
Improving AMR Parsing with Sequence-to-Sequence Pre-training
Dongqin Xu, Junhui Li, Muhua Zhu +2
In the literature, the research on abstract meaning representation (AMR) parsing is much restricted by the size of human-curated dataset which is critical to build an AMR parser wi…
Coupling Distant Annotation and Adversarial Training for Cross-Domain Chinese Word Segmentation
Ning Ding, Dingkun Long, Guangwei Xu +4
Fully supervised neural approaches have achieved significant progress in the task of Chinese word segmentation (CWS). Nevertheless, the performance of supervised models tends to dr…
Modeling Graph Structure in Transformer for Better AMR-to-Text Generation
Jie Zhu, Junhui Li, Muhua Zhu +3
Recent studies on AMR-to-text generation often formalize the task as a sequence-to-sequence (seq2seq) learning problem by converting an Abstract Meaning Representation (AMR) graph…
Deep Cascade Multi-task Learning for Slot Filling in Online Shopping Assistant
Yu Gong, Xusheng Luo, Yu Zhu +6
Slot filling is a critical task in natural language understanding (NLU) for dialog systems. State-of-the-art approaches treat it as a sequence labeling problem and adopt such model…
Learning When to Attend for Neural Machine Translation
Junhui Li, Muhua Zhu
In the past few years, attention mechanisms have become an indispensable component of end-to-end neural machine translation models. However, previous attention models always refer…
Modeling Source Syntax for Neural Machine Translation
Junhui Li, Deyi Xiong, Zhaopeng Tu +3
Even though a linguistics-free sequence to sequence model in neural machine translation (NMT) has certain capability of implicitly learning syntactic information of source sentence…