When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data Augmentation

17 March 2022

Papers citing "When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data Augmentation"

5 / 5 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
CILDA: Contrastive Data Augmentation using Intermediate Layer Knowledge Distillation Md. Akmal Haidar Mehdi Rezagholizadeh Abbas Ghaddar Khalil Bibi Philippe Langlais Pascal Poupart CLL 27 6 0 15 Apr 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 137 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