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MixText: Linguistically-Informed Interpolation of Hidden Space for
  Semi-Supervised Text Classification

MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification

25 April 2020
Jiaao Chen
Zichao Yang
Diyi Yang
    VLM
ArXivPDFHTML

Papers citing "MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification"

27 / 77 papers shown
Title
Challenging the Semi-Supervised VAE Framework for Text Classification
Challenging the Semi-Supervised VAE Framework for Text Classification
G. Felhi
Joseph Le Roux
Djamé Seddah
BDL
21
2
0
27 Sep 2021
Mitigating Data Scarceness through Data Synthesis, Augmentation and
  Curriculum for Abstractive Summarization
Mitigating Data Scarceness through Data Synthesis, Augmentation and Curriculum for Abstractive Summarization
Ahmed Magooda
Diane Litman
45
5
0
17 Sep 2021
Self-Training with Differentiable Teacher
Self-Training with Differentiable Teacher
Simiao Zuo
Yue Yu
Chen Liang
Haoming Jiang
Siawpeng Er
Chao Zhang
T. Zhao
H. Zha
41
14
0
15 Sep 2021
Learning Bill Similarity with Annotated and Augmented Corpora of Bills
Learning Bill Similarity with Annotated and Augmented Corpora of Bills
Jiseon Kim
Elden Griggs
In Song Kim
Alice H. Oh
AILaw
20
5
0
14 Sep 2021
Good-Enough Example Extrapolation
Good-Enough Example Extrapolation
Jason W. Wei
24
5
0
12 Sep 2021
Counterfactual Adversarial Learning with Representation Interpolation
Counterfactual Adversarial Learning with Representation Interpolation
Wen Wang
Wei Ping
Ning Shi
Jinfeng Li
Bingyu Zhu
Xiangyu Liu
Rongxin Zhang
AAML
OOD
CML
21
2
0
10 Sep 2021
Efficient Contrastive Learning via Novel Data Augmentation and
  Curriculum Learning
Efficient Contrastive Learning via Novel Data Augmentation and Curriculum Learning
Seonghyeon Ye
Jiseon Kim
Alice H. Oh
CLL
VLM
24
21
0
10 Sep 2021
Self-training Improves Pre-training for Few-shot Learning in
  Task-oriented Dialog Systems
Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog Systems
Fei Mi
Wanhao Zhou
Feng Cai
Lingjing Kong
Minlie Huang
Boi Faltings
27
32
0
28 Aug 2021
Noisy Channel Language Model Prompting for Few-Shot Text Classification
Noisy Channel Language Model Prompting for Few-Shot Text Classification
Sewon Min
Michael Lewis
Hannaneh Hajishirzi
Luke Zettlemoyer
VLM
28
218
0
09 Aug 2021
A Survey on Data Augmentation for Text Classification
A Survey on Data Augmentation for Text Classification
Markus Bayer
M. Kaufhold
Christian A. Reuter
36
334
0
07 Jul 2021
SSMix: Saliency-Based Span Mixup for Text Classification
SSMix: Saliency-Based Span Mixup for Text Classification
Soyoung Yoon
Gyuwan Kim
Kyumin Park
22
68
0
15 Jun 2021
An Empirical Survey of Data Augmentation for Limited Data Learning in
  NLP
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
Jiaao Chen
Derek Tam
Colin Raffel
Joey Tianyi Zhou
Diyi Yang
28
172
0
14 Jun 2021
Survey: Image Mixing and Deleting for Data Augmentation
Survey: Image Mixing and Deleting for Data Augmentation
Humza Naveed
Saeed Anwar
Munawar Hayat
Kashif Javed
Ajmal Mian
38
78
0
13 Jun 2021
Self-supervised Dialogue Learning for Spoken Conversational Question
  Answering
Self-supervised Dialogue Learning for Spoken Conversational Question Answering
Nuo Chen
Chenyu You
Yuexian Zou
SSL
22
33
0
04 Jun 2021
Out-of-Manifold Regularization in Contextual Embedding Space for Text
  Classification
Out-of-Manifold Regularization in Contextual Embedding Space for Text Classification
Seonghyeon Lee
Dongha Lee
Hwanjo Yu
19
4
0
14 May 2021
GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation
GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation
Kang Min Yoo
Dongju Park
Jaewook Kang
Sang-Woo Lee
Woomyeong Park
31
235
0
18 Apr 2021
Sentence Concatenation Approach to Data Augmentation for Neural Machine
  Translation
Sentence Concatenation Approach to Data Augmentation for Neural Machine Translation
Seiichiro Kondo
Kengo Hotate
Masahiro Kaneko
Mamoru Komachi
17
16
0
17 Apr 2021
Continual Learning for Text Classification with Information
  Disentanglement Based Regularization
Continual Learning for Text Classification with Information Disentanglement Based Regularization
Yufan Huang
Yanzhe Zhang
Jiaao Chen
Xuezhi Wang
Diyi Yang
CLL
17
106
0
12 Apr 2021
Improving and Simplifying Pattern Exploiting Training
Improving and Simplifying Pattern Exploiting Training
Derek Tam
Rakesh R Menon
Joey Tianyi Zhou
Shashank Srivastava
Colin Raffel
13
149
0
22 Mar 2021
A Primer on Contrastive Pretraining in Language Processing: Methods,
  Lessons Learned and Perspectives
A Primer on Contrastive Pretraining in Language Processing: Methods, Lessons Learned and Perspectives
Nils Rethmeier
Isabelle Augenstein
SSL
VLM
90
90
0
25 Feb 2021
Making Pre-trained Language Models Better Few-shot Learners
Making Pre-trained Language Models Better Few-shot Learners
Tianyu Gao
Adam Fisch
Danqi Chen
243
1,919
0
31 Dec 2020
Sequence-Level Mixed Sample Data Augmentation
Sequence-Level Mixed Sample Data Augmentation
Demi Guo
Yoon Kim
Alexander M. Rush
25
98
0
18 Nov 2020
Text Classification Using Label Names Only: A Language Model
  Self-Training Approach
Text Classification Using Label Names Only: A Language Model Self-Training Approach
Yu Meng
Yunyi Zhang
Jiaxin Huang
Chenyan Xiong
Heng Ji
Chao Zhang
Jiawei Han
VLM
55
75
0
14 Oct 2020
Controlling the Interaction Between Generation and Inference in
  Semi-Supervised Variational Autoencoders Using Importance Weighting
Controlling the Interaction Between Generation and Inference in Semi-Supervised Variational Autoencoders Using Importance Weighting
G. Felhi
Joseph Leroux
Djamé Seddah
BDL
21
1
0
13 Oct 2020
A Simple but Tough-to-Beat Data Augmentation Approach for Natural
  Language Understanding and Generation
A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation
Dinghan Shen
Ming Zheng
Yelong Shen
Yanru Qu
Weizhu Chen
AAML
29
130
0
29 Sep 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural
  Language Inference
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference
Timo Schick
Hinrich Schütze
258
1,589
0
21 Jan 2020
Mean teachers are better role models: Weight-averaged consistency
  targets improve semi-supervised deep learning results
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen
Harri Valpola
OOD
MoMe
264
1,275
0
06 Mar 2017
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