Text Augmentation
34 papers with code • 0 benchmarks • 0 datasets
You can read these blog posts to get an overview of the approaches.
Benchmarks
These leaderboards are used to track progress in Text Augmentation
Libraries
Use these libraries to find Text Augmentation models and implementationsLatest papers
Story Visualization by Online Text Augmentation with Context Memory
Story visualization (SV) is a challenging text-to-image generation task for the difficulty of not only rendering visual details from the text descriptions but also encoding a long-term context across multiple sentences.
STA: Self-controlled Text Augmentation for Improving Text Classifications
Despite recent advancements in Machine Learning, many tasks still involve working in low-data regimes which can make solving natural language problems difficult.
RPN: A Word Vector Level Data Augmentation Algorithm in Deep Learning for Language Understanding
DLYuanGod/RPN
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However, existing data augmentation techniques in natural language understanding (NLU) may not fully capture the complexity of natural language variations, and they can be challenging to apply to large datasets.
BootAug: Boosting Text Augmentation via Hybrid Instance Filtering Framework
Our experimental results on three classification tasks and nine public datasets show that BootAug addresses the performance drop problem and outperforms state-of-the-art text augmentation methods.
Zemi: Learning Zero-Shot Semi-Parametric Language Models from Multiple Tasks
Notably, our proposed $\text{Zemi}_\text{LARGE}$ outperforms T0-3B by 16% on all seven evaluation tasks while being 3. 9x smaller in model size.
Adaptation of domain-specific transformer models with text oversampling for sentiment analysis of social media posts on Covid-19 vaccines
ace117mc/transformer-models-covid
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Covid-19 has spread across the world and several vaccines have been developed to counter its surge.
DoubleMix: Simple Interpolation-Based Data Augmentation for Text Classification
declare-lab/doublemix
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COLING 2022
This paper proposes a simple yet effective interpolation-based data augmentation approach termed DoubleMix, to improve the robustness of models in text classification.
Selective Text Augmentation with Word Roles for Low-Resource Text Classification
beyondguo/STA
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Different words may play different roles in text classification, which inspires us to strategically select the proper roles for text augmentation.
BAN-Cap: A Multi-Purpose English-Bangla Image Descriptions Dataset
faiyazkhan11/ban-cap
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LREC 2022
As computers have become efficient at understanding visual information and transforming it into a written representation, research interest in tasks like automatic image captioning has seen a significant leap over the last few years.
Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning
snap-research/mmvid
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CVPR 2022
In addition, our model can extract visual information as suggested by the text prompt, e. g., "an object in image one is moving northeast", and generate corresponding videos.
