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data augmentation

3037 papers

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Also known as

DA-MCMC DADA DA TTA ADA EDA

Co-occurring keywords

text classification (6776) large language model (12755) transfer learning (5442) semi-supervised learning (2331) few-shot learning (3390) domain adaptation (4578) machine translation (2472) image classification (1943) language model (4573) low-resource language (2234)

Papers

The ARC-NKUA Submission for the English-Ukrainian General Machine Translation Shared Task at WMT22 EMNLP 2022
DUTNLP Machine Translation System for WMT22 General MT Task EMNLP 2022
Vega-MT: The JD Explore Academy Machine Translation System for WMT22 EMNLP 2022
Data Augmentation for Inline Tag-Aware Neural Machine Translation EMNLP 2022
Tackling Low-Resourced Sign Language Translation: UPC at WMT-SLT 22 EMNLP 2022
Improved Data Augmentation for Translation Suggestion EMNLP 2022
Experimental Machine Translation of the Swiss German Sign Language via 3D Augmentation of Body Keypoints EMNLP 2022
On The Arabic Dialects’ Identification: Overcoming Challenges of Geographical Similarities Between Arabic dialects and Imbalanced Datasets EMNLP 2022
Divide-and-Conquer Text Simplification by Scalable Data Enhancement EMNLP 2022
AIM: An Auto-Augmenter for Images and Meshes CVPR 2022
AlignMixup: Improving Representations by Interpolating Aligned Features CVPR 2022
SwapMix: Diagnosing and Regularizing the Over-Reliance on Visual Context in Visual Question Answering CVPR 2022
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification NIPS 2022
GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks NIPS 2022
MEMO: Test Time Robustness via Adaptation and Augmentation NIPS 2022
Spectral Bias in Practice: The Role of Function Frequency in Generalization NIPS 2022
TokenMixup: Efficient Attention-guided Token-level Data Augmentation for Transformers NIPS 2022
Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome NIPS 2022
Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach NIPS 2022
SageMix: Saliency-Guided Mixup for Point Clouds NIPS 2022
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This? NIPS 2022
Deep invariant networks with differentiable augmentation layers NIPS 2022
FeLMi : Few shot Learning with hard Mixup NIPS 2022
Open High-Resolution Satellite Imagery: The WorldStrat Dataset – With Application to Super-Resolution NIPS 2022
Data-Efficient Augmentation for Training Neural Networks NIPS 2022