24 citations · 79 across the 9 of their papers we have counts for
12 papers
Leveraging Expert Guided Adversarial Augmentation For Improving Generalization in Named Entity Recognition
Aaron Reich, Jiaao Chen, Aastha Agrawal +2
Named Entity Recognition (NER) systems often demonstrate great performance on in-distribution data, but perform poorly on examples drawn from a shifted distribution. One way to eva…
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
Jiaao Chen, Derek Tam, Colin Raffel +2
NLP has achieved great progress in the past decade through the use of neural models and large labeled datasets. The dependence on abundant data prevents NLP models from being appli…
HiddenCut: Simple Data Augmentation for Natural Language Understanding with Better Generalization
Jiaao Chen, Dinghan Shen, Weizhu Chen +1
Fine-tuning large pre-trained models with task-specific data has achieved great success in NLP. However, it has been demonstrated that the majority of information within the self-a…
Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs
Jiaao Chen, Diyi Yang
Abstractive conversation summarization has received much attention recently. However, these generated summaries often suffer from insufficient, redundant, or incorrect content, lar…
Continual Learning for Text Classification with Information Disentanglement Based Regularization
Yufan Huang, Yanzhe Zhang, Jiaao Chen +2
Continual learning has become increasingly important as it enables NLP models to constantly learn and gain knowledge over time. Previous continual learning methods are mainly desig…
Weakly-Supervised Hierarchical Models for Predicting Persuasive Strategies in Good-faith Textual Requests
Jiaao Chen, Diyi Yang
Modeling persuasive language has the potential to better facilitate our decision-making processes. Despite its importance, computational modeling of persuasion is still in its infa…