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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 51–75 of 97 papers

TitleStatusHype
Iterative Mask Filling: An Effective Text Augmentation Method Using Masked Language Modeling—0
TextAug: Test time Text Augmentation for Multimodal Person Re-identification—0
What Have Been Learned & What Should Be Learned? An Empirical Study of How to Selectively Augment Text for Classification—0
Text Data Augmentation: Towards better detection of spear-phishing emails—0
LLMs vs Established Text Augmentation Techniques for Classification: When do the Benefits Outweight the Costs?—0
LLMvsSmall Model? Large Language Model Based Text Augmentation Enhanced Personality Detection Model—0
Mitigating Data Imbalance for Software Vulnerability Assessment: Does Data Augmentation Help?—0
Back Translation Survey for Improving Text Augmentation—0
Multimodal AI on Wound Images and Clinical Notes for Home Patient Referral—0
Neural Data-to-Text Generation with LM-based Text Augmentation—0
On the Effectiveness of Neural Text Generation based Data Augmentation for Recognition of Morphologically Rich Speech—0
Augmenting emotion features in irony detection with Large language modeling—0
Performance Improvement of Language-Queried Audio Source Separation Based on Caption Augmentation From Large Language Models for DCASE Challenge 2024 Task 9—0
Prediction of ICD Codes with Clinical BERT Embeddings and Text Augmentation with Label Balancing using MIMIC-III—0
Augment, Drop & Swap: Improving Diversity in LLM Captions for Efficient Music-Text Representation Learning—0
Probabilistic Linguistic Knowledge and Token-level Text Augmentation—0
QAEA-DR: A Unified Text Augmentation Framework for Dense Retrieval—0
RESMatch: Referring Expression Segmentation in a Semi-Supervised Manner—0
Robust Authorship Verification with Transfer Learning—0
Roles of Words: What Should (n’t) Be Augmented in Text Augmentation on Text Classification Tasks?—0
Text Generation with Speech Synthesis for ASR Data Augmentation—0
To Augment or Not to Augment? A Comparative Study on Text Augmentation Techniques for Low-Resource NLP—0
Toward General and Robust LLM-enhanced Text-attributed Graph Learning—0
Adversarial Evaluation of Multimodal Models under Realistic Gray Box Assumption—0
An Experimental Study on Data Augmentation Techniques for Named Entity Recognition on Low-Resource Domains—0
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