4 papers
On Predicting Vulnerability Severity Using In-Context Learning: An Industrial Case Study
Daniel Rodriguez-Cardenas, David Nader Palacio, Anna Schmedding +8
Modern software systems require earlier and more scalable vulnerability severity assessment to reduce exposure to high-impact security flaws. Security analysts typically assign CVS…
Beyond Pixels: Introspective and Interactive Grounding for Visualization Agents
Yiyang Lu, Woong Shin, Ahmad Maroof Karimi +3
Vision-Language Models (VLMs) frequently misread values, hallucinate details, and confuse overlapping elements in charts. Current approaches rely solely on pixel interpretation, cr…
Black-box Adversarial Attacks on CNN-based SLAM Algorithms
Maria Rafaela Gkeka, Bowen Sun, Evgenia Smirni +3
Continuous advancements in deep learning have led to significant progress in feature detection, resulting in enhanced accuracy in tasks like Simultaneous Localization and Mapping (…
Safety Interventions against Adversarial Patches in an Open-Source Driver Assistance System
Cheng Chen, Grant Xiao, Daehyun Lee +4
Drivers are becoming increasingly reliant on advanced driver assistance systems (ADAS) as autonomous driving technology becomes more popular and developed with advanced safety feat…