Adversarial training capability added for semi-supervised text classification

AI Impact Summary

This change introduces adversarial training methods for semi-supervised text classification, enabling models to leverage unlabeled data with generated adversarial examples to improve robustness. It can boost accuracy in low-label domains and reduce labeling costs, but demands updates to training pipelines, data handling, and evaluation to validate robustness gains. Expect higher training complexity and the need for careful hyperparameter tuning to ensure stable convergence and avoid unintended trade-offs.