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Text Augmentation

You can read these blog posts to get an overview of the approaches.

Papers

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Showing 76–97 of 97 papers

TitleStatusHype
BrightCookies at SemEval-2025 Task 9: Exploring Data Augmentation for Food Hazard ClassificationCode0
Contextual Augmentation: Data Augmentation by Words with Paradigmatic RelationsCode0
COVID-19 Vaccine Misinformation in Middle Income CountriesCode0
Data Augmentation via Dependency Tree Morphing for Low-Resource LanguagesCode0
Distributional Data Augmentation Methods for Low Resource LanguageCode0
EDDA: A Encoder-Decoder Data Augmentation Framework for Zero-Shot Stance DetectionCode0
Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentationCode0
Empirical Study of Text Augmentation on Social Media Text in VietnameseCode0
From Big to Small Without Losing It All: Text Augmentation with ChatGPT for Efficient Sentiment AnalysisCode0
Adaptation of domain-specific transformer models with text oversampling for sentiment analysis of social media posts on Covid-19 vaccinesCode0
Laser: Efficient Language-Guided Segmentation in Neural Radiance FieldsCode0
Learning to Compose Domain-Specific Transformations for Data AugmentationCode0
Linguistic Knowledge in Data Augmentation for Natural Language Processing: An Example on Chinese Question MatchingCode0
RPN: A Word Vector Level Data Augmentation Algorithm in Deep Learning for Language UnderstandingCode0
Selective Text Augmentation with Word Roles for Low-Resource Text ClassificationCode0
Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog SystemsCode0
Sequence-to-Sequence Data Augmentation for Dialogue Language UnderstandingCode0
STA: Self-controlled Text Augmentation for Improving Text ClassificationsCode0
Teaching Specific Scientific Knowledge into Large Language Models through Additional TrainingCode0
Text Data Augmentation Made Simple By Leveraging NLP Cloud APIsCode0
UCD-CS at TREC 2021 Incident Streams TrackCode0
Use Random Selection for Now: Investigation of Few-Shot Selection Strategies in LLM-based Text Augmentation for ClassificationCode0
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