Who Cited It

Unsupervised Data Augmentation for Consistency Training

2019 · arXiv (Cornell University) · 1,624 citations · 7 from inside this corpus

Qizhe Xie low, Zihang Dai, Eduard Hovy, Minh-Thang Luong low, Quoc V. Le

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Unsupervised Data Augmentation for Consistency Training (2019)Unsupervised Data Augmentatio…Glove: Global Vectors for Word Representation (2014)Glove: Global Vectors for Wor…BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (2019)BERT: Pre-training of Deep Bi…Xception: Deep Learning with Depthwise Separable Convolutions (2017)Xception: Deep Learning with …Distributed Representations of Words and Phrases and their Compositionality (2013)Distributed Representations o…Distilling the Knowledge in a Neural Network (2015)Distilling the Knowledge in a…Semi-Supervised Classification with Graph Convolutional Networks (2016)Semi-Supervised Classificatio…Attention Is All You Need (2025)Attention Is All You NeedA unified architecture for natural language processing (2008)A unified architecture for na…mixup: Beyond Empirical Risk Minimization (2017)mixup: Beyond Empirical Risk …SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition (2019)SpecAugment: A Simple Data Au…Learning Word Vectors for Sentiment Analysis (2011)Learning Word Vectors for Sen…Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised … (2018)Virtual Adversarial Training:…[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)][No title in the source recor…Deep Contextualized Word Representations (2018)Deep Contextualized Word Repr…Deep Speech: Scaling up end-to-end speech recognition (2014)Deep Speech: Scaling up end-t…A Simple Framework for Contrastive Learning of Visual Representations (2020)A Simple Framework for Contra…Emerging Properties in Self-Supervised Vision Transformers (2021)Emerging Properties in Self-S…Language Models are Few-Shot Learners (2020)Language Models are Few-Shot …FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence (2020)FixMatch: Simplifying Semi-Su…Longformer: The Long-Document Transformer (2020)Longformer: The Long-Document…XLNet: Generalized Autoregressive Pretraining for Language Understanding (2019)XLNet: Generalized Autoregres…Text Data Augmentation for Deep Learning (2021)Text Data Augmentation for De…
22 of 22 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Glove: Global Vectors for Word Representation201434,067
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding201933,416
Xception: Deep Learning with Depthwise Separable Convolutions201719,457
Distributed Representations of Words and Phrases and their Compositionality201318,054
Distilling the Knowledge in a Neural Network201514,099
Semi-Supervised Classification with Graph Convolutional Networks20168,058
Attention Is All You Need20257,133
A unified architecture for natural language processing20085,207
mixup: Beyond Empirical Risk Minimization20174,806
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition20193,619
Learning Word Vectors for Sentiment Analysis20113,294
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised …20182,873
[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]2,485
Deep Contextualized Word Representations20181,783
Deep Speech: Scaling up end-to-end speech recognition20141,519

What cites it, inside the corpus

PaperYearCited
A Simple Framework for Contrastive Learning of Visual Representations20207,341
Emerging Properties in Self-Supervised Vision Transformers20215,394
Language Models are Few-Shot Learners20203,020
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence20202,271
Longformer: The Long-Document Transformer20202,206
XLNet: Generalized Autoregressive Pretraining for Language Understanding20191,854
Text Data Augmentation for Deep Learning20211,701

Links

DOI · Open access copy · OpenAlex record

Topics

Domain Adaptation and Few-Shot LearningComputer Science
Multimodal Machine Learning ApplicationsComputer Science
Topic ModelingComputer Science

Is this record sound?

partial

One field of this record is missing or disagrees with another. What is shown below is what the source publishes.

  • supports5 author record(s) attached.
  • supports74 reference(s) recorded.
  • weakensThe DOI names 1904 but the record dates this to 2,019. One of the two is about a different paper.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:56+00:00.

sha256 7bc26169e93749d1…