3 papers
cs.CL2025
Universal Adversarial Suffixes for Language Models Using Reinforcement Learning with Calibrated Reward
Sampriti Soor, Suklav Ghosh, Arijit Sur
Language models are vulnerable to short adversarial suffixes that can reliably alter predictions. Previous works usually find such suffixes with gradient search or rule-based metho…
cs.CL2025
Universal Adversarial Suffixes Using Calibrated Gumbel-Softmax Relaxation
Sampriti Soor, Suklav Ghosh, Arijit Sur
Language models (LMs) are often used as zero-shot or few-shot classifiers by scoring label words, but they remain fragile to adversarial prompts. Prior work typically optimizes tas…
cs.CV2025
Trans-defense: Transformer-based Denoiser for Adversarial Defense with Spatial-Frequency Domain Representation
Alik Pramanick, Mayank Bansal, Utkarsh Srivastava +2
In recent times, deep neural networks (DNNs) have been successfully adopted for various applications. Despite their notable achievements, it has become evident that DNNs are vulner…