1) Establishing a theoretical framework connecting differential geometry with language model data augmentation; 2) Developing a toolkit for diffeomorphic data augmentation usable in large language model pre-training and fine-tuning; 3) Providing empirical evidence on how this method improves model performance in low-resource scenarios and adversarial environments
Text Transformation
Innovative algorithms for preserving semantic invariance in text.
Diffeomorphic Augmentation
Enhancing models with advanced text transformation techniques.
Experimental Validation
Comparative experiments with traditional and advanced methods.