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How Effective is Task-Agnostic Data Augmentation for Pretrained
  Transformers?

How Effective is Task-Agnostic Data Augmentation for Pretrained Transformers?

5 October 2020
Shayne Longpre
Yu Wang
Christopher DuBois
    ViT
ArXivPDFHTML

Papers citing "How Effective is Task-Agnostic Data Augmentation for Pretrained Transformers?"

15 / 15 papers shown
Title
Approximate Nearest Neighbor Negative Contrastive Learning for Dense
  Text Retrieval
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
Lee Xiong
Chenyan Xiong
Ye Li
Kwok-Fung Tang
Jialin Liu
Paul N. Bennett
Junaid Ahmed
Arnold Overwijk
114
1,224
0
01 Jul 2020
Contextual Embeddings: When Are They Worth It?
Contextual Embeddings: When Are They Worth It?
Simran Arora
Avner May
Jian Zhang
Christopher Ré
41
61
0
18 May 2020
Fine-Tuning Pretrained Language Models: Weight Initializations, Data
  Orders, and Early Stopping
Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping
Jesse Dodge
Gabriel Ilharco
Roy Schwartz
Ali Farhadi
Hannaneh Hajishirzi
Noah A. Smith
95
595
0
15 Feb 2020
An Exploration of Data Augmentation and Sampling Techniques for
  Domain-Agnostic Question Answering
An Exploration of Data Augmentation and Sampling Techniques for Domain-Agnostic Question Answering
Shayne Longpre
Yi Lu
Zhucheng Tu
Christopher DuBois
50
70
0
04 Dec 2019
Generalized Data Augmentation for Low-Resource Translation
Generalized Data Augmentation for Low-Resource Translation
Mengzhou Xia
X. Kong
Antonios Anastasopoulos
Graham Neubig
65
120
0
10 Jun 2019
Unsupervised Data Augmentation for Consistency Training
Unsupervised Data Augmentation for Consistency Training
Qizhe Xie
Zihang Dai
Eduard H. Hovy
Minh-Thang Luong
Quoc V. Le
129
2,314
0
29 Apr 2019
Data Augmentation for BERT Fine-Tuning in Open-Domain Question Answering
Data Augmentation for BERT Fine-Tuning in Open-Domain Question Answering
Wei Yang
Yuqing Xie
Luchen Tan
Kun Xiong
Ming Li
Jimmy J. Lin
RALM
OOD
41
64
0
14 Apr 2019
EDA: Easy Data Augmentation Techniques for Boosting Performance on Text
  Classification Tasks
EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
Jason W. Wei
Kai Zou
107
1,953
0
31 Jan 2019
Scaling Neural Machine Translation
Scaling Neural Machine Translation
Myle Ott
Sergey Edunov
David Grangier
Michael Auli
AIMat
172
614
0
01 Jun 2018
AutoAugment: Learning Augmentation Policies from Data
AutoAugment: Learning Augmentation Policies from Data
E. D. Cubuk
Barret Zoph
Dandelion Mané
Vijay Vasudevan
Quoc V. Le
120
1,771
0
24 May 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
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
1.1K
7,154
0
20 Apr 2018
Annotation Artifacts in Natural Language Inference Data
Annotation Artifacts in Natural Language Inference Data
Suchin Gururangan
Swabha Swayamdipta
Omer Levy
Roy Schwartz
Samuel R. Bowman
Noah A. Smith
147
1,177
0
06 Mar 2018
The Effectiveness of Data Augmentation in Image Classification using
  Deep Learning
The Effectiveness of Data Augmentation in Image Classification using Deep Learning
Luis Perez
Jason Wang
80
2,788
0
13 Dec 2017
A Broad-Coverage Challenge Corpus for Sentence Understanding through
  Inference
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference
Adina Williams
Nikita Nangia
Samuel R. Bowman
520
4,476
0
18 Apr 2017
Improving Neural Machine Translation Models with Monolingual Data
Improving Neural Machine Translation Models with Monolingual Data
Rico Sennrich
Barry Haddow
Alexandra Birch
246
2,717
0
20 Nov 2015
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