9 papers
From Steering to Pedalling: Do Autonomous Driving VLMs Generalize to Cyclist-Assistive Spatial Perception and Planning?
Krishna Kanth Nakka, Vedasri Nakka
Cyclists often encounter safety-critical situations in urban traffic, highlighting the need for assistive systems that support safe and informed decision-making. Recently, vision-l…
NAT: Learning to Attack Neurons for Enhanced Adversarial Transferability
Krishna Kanth Nakka, Alexandre Alahi
The generation of transferable adversarial perturbations typically involves training a generator to maximize embedding separation between clean and adversarial images at a single m…
PII-Compass: Guiding LLM training data extraction prompts towards the target PII via grounding
Krishna Kanth Nakka, Ahmed Frikha, Ricardo Mendes +2
The latest and most impactful advances in large models stem from their increased size. Unfortunately, this translates into an improved memorization capacity, raising data privacy c…
PII Jailbreaking in LLMs via Activation Steering Reveals Personal Information Leakage
Krishna Kanth Nakka, Xue Jiang, Dmitrii Usynin +1
This paper investigates privacy jailbreaking in LLMs via steering, focusing on whether manipulating activations can bypass LLM alignment and alter response behaviors to privacy rel…
Mammo-SAE: Interpreting Breast Cancer Concept Learning with Sparse Autoencoders
Krishna Kanth Nakka
Interpretability is critical in high-stakes domains such as medical imaging, where understanding model decisions is essential for clinical adoption. In this work, we introduce Spar…
PII-Scope: A Comprehensive Study on Training Data PII Extraction Attacks in LLMs
Krishna Kanth Nakka, Ahmed Frikha, Ricardo Mendes +2
In this work, we introduce PII-Scope, a comprehensive benchmark designed to evaluate state-of-the-art methodologies for PII extraction attacks targeting LLMs across diverse threat…