10 citations · 11 across the 6 of their papers we have counts for
6 papers
Style Transfer as Data Augmentation: A Case Study on Named Entity Recognition
Shuguang Chen, Leonardo Neves, Thamar Solorio
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 di…
CALCS 2021 Shared Task: Machine Translation for Code-Switched Data
Shuguang Chen, Gustavo Aguilar, Anirudh Srinivasan +2
To date, efforts in the code-switching literature have focused for the most part on language identification, POS, NER, and syntactic parsing. In this paper, we address machine tran…
Data Augmentation for Cross-Domain Named Entity Recognition
Shuguang Chen, Gustavo Aguilar, Leonardo Neves +1
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-doma…
A Simple Approach to Jointly Rank Passages and Select Relevant Sentences in the OBQA Context
Man Luo, Shuguang Chen, Chitta Baral
In the open book question answering (OBQA) task, selecting the relevant passages and sentences from distracting information is crucial to reason the answer to a question. HotpotQA…
Mitigating Temporal-Drift: A Simple Approach to Keep NER Models Crisp
Shuguang Chen, Leonardo Neves, Thamar Solorio
Performance of neural models for named entity recognition degrades over time, becoming stale. This degradation is due to temporal drift, the change in our target variables' statist…
Can images help recognize entities? A study of the role of images for Multimodal NER
Shuguang Chen, Gustavo Aguilar, Leonardo Neves +1
Multimodal named entity recognition (MNER) requires to bridge the gap between language understanding and visual context. While many multimodal neural techniques have been proposed…