3 citations · 4 across the 5 of their papers we have counts for
5 papers · 1 filter
AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing
Asaad Alghamdi, Xinyu Duan, Wei Jiang +9
Developing monolingual large Pre-trained Language Models (PLMs) is shown to be very successful in handling different tasks in Natural Language Processing (NLP). In this work, we pr…
A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends
Xiaoye Qu, Yingjie Gu, Qingrong Xia +3
As more and more Arabic texts emerged on the Internet, extracting important information from these Arabic texts is especially useful. As a fundamental technology, Named entity reco…
MuCPAD: A Multi-Domain Chinese Predicate-Argument Dataset
Yahui Liu, Haoping Yang, Chen Gong +3
During the past decade, neural network models have made tremendous progress on in-domain semantic role labeling (SRL). However, performance drops dramatically under the out-of-doma…
A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling
Qingrong Xia, Zhenghua Li, Min Zhang
Semantic role labeling (SRL) aims to identify the predicate-argument structure of a sentence. Inspired by the strong correlation between syntax and semantics, previous works pay mu…
Syntax-aware Neural Semantic Role Labeling
Qingrong Xia, Zhenghua Li, Min Zhang +4
Semantic role labeling (SRL), also known as shallow semantic parsing, is an important yet challenging task in NLP. Motivated by the close correlation between syntactic and semantic…