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Found 5 papers, 1 papers with code
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.
Investigating Semi-Supervised Learning Algorithms in Text Datasets
SSL methods that use data augmentation are most successful for image datasets.
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.
Developing and Evaluating Tiny to Medium-Sized Turkish BERT Models
This study introduces and evaluates tiny, mini, small, and medium-sized uncased Turkish BERT models, aiming to bridge the research gap in less-resourced languages.
A Robust Optimization Method for Label Noisy Datasets Based on Adaptive Threshold: Adaptive-k
SGD does not produce robust results on datasets with label noise.
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