Text Augmentation
33 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 with no code
Augmenting emotion features in irony detection with Large language modeling
This study introduces a novel method for irony detection, applying Large Language Models (LLMs) with prompt-based learning to facilitate emotion-centric text augmentation.
LLMvsSmall Model? Large Language Model Based Text Augmentation Enhanced Personality Detection Model
Furthermore, we utilize the LLM to enrich the information of personality labels for enhancing the detection performance.
Advancing NLP Models with Strategic Text Augmentation: A Comprehensive Study of Augmentation Methods and Curriculum Strategies
The study concludes that the use of augmentation methods, especially in conjunction with MCCL, leads to improved results in various classification tasks, providing a foundation for future advances in text augmentation strategies in NLP.
Evaluation Metrics for Text Data Augmentation in NLP
Recent surveys on data augmentation for natural language processing have reported different techniques and advancements in the field.
RESMatch: Referring Expression Segmentation in a Semi-Supervised Manner
This pioneering work lays the groundwork for future research in semi-supervised learning for referring expression segmentation.
IndiText Boost: Text Augmentation for Low Resource India Languages
In this work, we focus on implementing techniques like Easy Data Augmentation, Back Translation, Paraphrasing, Text Generation using LLMs, and Text Expansion using LLMs for text classification on different languages.
Iterative Mask Filling: An Effective Text Augmentation Method Using Masked Language Modeling
Data augmentation is an effective technique for improving the performance of machine learning models.
Augmenty: A Python Library for Structured Text Augmentation
Augmnety is a Python library for structured text augmentation.
TextAug: Test time Text Augmentation for Multimodal Person Re-identification
In this study, we investigate the effectiveness of two computer vision data augmentation techniques: cutout and cutmix, for text augmentation in multi-modal person re-identification.
CLAP: Isolating Content from Style through Contrastive Learning with Augmented Prompts
To address this limitation, we adopt a causal generative perspective for multimodal data and propose contrastive learning with data augmentation to disentangle content features from the original representations.
