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A survey on data augmentation for text classification
Data augmentation, the artificial creation of training data for machine learning by
transformations, is a widely studied research field across machine learning disciplines …
transformations, is a widely studied research field across machine learning disciplines …
A comprehensive survey on data augmentation
Z Wang, P Wang, K Liu, P Wang, Y Fu, CT Lu… - ar** language-image pre-training for unified vision-language understanding and generation
Abstract Vision-Language Pre-training (VLP) has advanced the performance for many vision-
language tasks. However, most existing pre-trained models only excel in either …
language tasks. However, most existing pre-trained models only excel in either …
A survey of data augmentation approaches for NLP
Data augmentation has recently seen increased interest in NLP due to more work in low-
resource domains, new tasks, and the popularity of large-scale neural networks that require …
resource domains, new tasks, and the popularity of large-scale neural networks that require …
Scaling laws of synthetic images for model training... for now
Recent significant advances in text-to-image models unlock the possibility of training vision
systems using synthetic images potentially overcoming the difficulty of collecting curated …
systems using synthetic images potentially overcoming the difficulty of collecting curated …
Leveraging large language models for multiple choice question answering
J Robinson, CM Rytting, D Wingate - arxiv preprint arxiv:2210.12353, 2022 - arxiv.org
While large language models (LLMs) like GPT-3 have achieved impressive results on
multiple choice question answering (MCQA) tasks in the zero, one, and few-shot settings …
multiple choice question answering (MCQA) tasks in the zero, one, and few-shot settings …
Learning vision from models rivals learning vision from data
We introduce SynCLR a novel approach for learning visual representations exclusively from
synthetic images without any real data. We synthesize a large dataset of image captions …
synthetic images without any real data. We synthesize a large dataset of image captions …