← Search

Shuguang Chen

2 accepted papers

2022

Style Transfer as Data Augmentation: A Case Study on Named Entity Recognition

EMNLP 2022main

In this work, we take the named entity recognition task in the English language as a case study and explore style transfer as a data augmentation method to increase the size and diversity of training data in low-resource scenarios. We propose a new method to effectively transform the text from a hig…

2021

Data Augmentation for Cross-Domain Named Entity Recognition

EMNLP 2021main

Current work in named entity recognition (NER) shows that data augmentation techniques can produce more robust models. However, most existing techniques focus on augmenting in-domain data in low-resource scenarios where annotated data is quite limited. In this work, we take this research direction t…