13 citations · 27 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 13 cited
Convolution-enhanced Evolving Attention Networks
Yujing Wang, Yaming Yang, Zhuo Li +7
Attention-based neural networks, such as Transformers, have become ubiquitous in numerous applications, including computer vision, natural language processing, and time-series anal…
cs.CL2021★ 4 cited
Syntax-BERT: Improving Pre-trained Transformers with Syntax Trees
Jiangang Bai, Yujing Wang, Yiren Chen +4
Pre-trained language models like BERT achieve superior performances in various NLP tasks without explicit consideration of syntactic information. Meanwhile, syntactic information h…
cs.LG2021★ 10 cited
Evolving Attention with Residual Convolutions
Yujing Wang, Yaming Yang, Jiangang Bai +6
Transformer is a ubiquitous model for natural language processing and has attracted wide attentions in computer vision. The attention maps are indispensable for a transformer model…