This paper introduces BERTGuard, a text classification framework that enhances the resilience of BERT models against adversarial attacks through feature trimming and sub-sampling within an adversarial training framework. Our approach outperforms the baseline BERT models against various augmented white-box adversarial attacks. Its resiliency is demonstrated using the benchmark IMDB movie review dataset.

It’s important to note that the classification of epileptic seizures can be complex, and an individual may experience more than one type of  seizure. Additionally, advancements in understanding epilepsy may lead  to refinements in the classification system over time. If someone is  experiencing seizures, it’s crucial for them to consult with a  healthcare professional for a proper diagnosis and appropriate  treatment.Â