2 papers
cs.CL2025
Contextual Breach: Assessing the Robustness of Transformer-based QA Models
Asir Saadat, Nahian Ibn Asad
Contextual question-answering models are susceptible to adversarial perturbations to input context, commonly observed in real-world scenarios. These adversarial noises are designed…
cs.CV2025
FUSED-Net: Detecting Traffic Signs with Limited Data
Md. Atiqur Rahman, Nahian Ibn Asad, Md. Mushfiqul Haque Omi +3
Automatic Traffic Sign Recognition is paramount in modern transportation systems, motivating several research endeavors to focus on performance improvement by utilizing large-scale…