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When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data Augmentation
17 March 2022
Ehsan Kamalloo
Mehdi Rezagholizadeh
A. Ghodsi
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Papers citing
"When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data Augmentation"
4 / 4 papers shown
Title
On-the-fly Denoising for Data Augmentation in Natural Language Understanding
Tianqing Fang
Wenxuan Zhou
Fangyu Liu
Hongming Zhang
Yangqiu Song
Muhao Chen
36
1
0
20 Dec 2022
RAIL-KD: RAndom Intermediate Layer Mapping for Knowledge Distillation
Md. Akmal Haidar
Nithin Anchuri
Mehdi Rezagholizadeh
Abbas Ghaddar
Philippe Langlais
Pascal Poupart
31
22
0
21 Sep 2021
CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding
Yanru Qu
Dinghan Shen
Yelong Shen
Sandra Sajeev
Jiawei Han
Weizhu Chen
134
66
0
16 Oct 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Jinpeng Wang
Amanpreet Singh
Julian Michael
Felix Hill
Omer Levy
Samuel R. Bowman
ELM
297
6,956
0
20 Apr 2018
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