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Adversarial Text Purification: Large Language Model Approach for Defense
Background Adversarial purification is a defense mechanism for safe-guarding classifiers against adversarial attacks without knowing the type of attacks or training of the classifier. These techniques analyze and eliminate adversarial perturbations from the attacked inputs, and help to restore purified samples that retain similarity to the attacked...
Published: 6/27/2025   |   Inventor(s): Raha Moraffah, Shubh Khandelwal, Amrita Bhattacharjee, Huan Liu
Keywords(s): Artificial Intelligence, Defense Applications, Machine Learning, Natural Language Processing, Security, Text Mining
Category(s): Physical Science, Artificial Intelligence/Machine Learning, Applied Technologies, Cybersecurity