activity
20172024
most citedImproving AMR Parsing with Sequence-to-Sequence Pre-training

6 citations · 7 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL2024

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…

cs.CL2021

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…

cs.CL20206 cited

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…

cs.CL2020

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…

cs.CL2019

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…

cs.CL2018

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…