49 citations · 72 across the 9 of their papers we have counts for
4 papers · 1 filter
Few-Shot Text Classification with Triplet Networks, Data Augmentation, and Curriculum Learning
Jason Wei, Chengyu Huang, Soroush Vosoughi +2
Few-shot text classification is a fundamental NLP task in which a model aims to classify text into a large number of categories, given only a few training examples per category. Th…
Text Augmentation in a Multi-Task View
Jason Wei, Chengyu Huang, Shiqi Xu +1
Traditional data augmentation aims to increase the coverage of the input distribution by generating augmented examples that strongly resemble original samples in an online fashion…
An Empirical Survey of Unsupervised Text Representation Methods on Twitter Data
Lili Wang, Chongyang Gao, Jason Wei +3
The field of NLP has seen unprecedented achievements in recent years. Most notably, with the advent of large-scale pre-trained Transformer-based language models, such as BERT, ther…
EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
Jason Wei, Kai Zou
We present EDA: easy data augmentation techniques for boosting performance on text classification tasks. EDA consists of four simple but powerful operations: synonym replacement, r…