1 citations · 1 across the 12 of their papers we have counts for
12 papers
DiffRadar: Differentiable Physics-Aware Radar SLAM with Gaussian Fields
Gaurav Bagwe, Xiaoyong Yuan, Yongji Wu +1
Radar sensing is increasingly used in mobile systems because it operates reliably under poor lighting, adverse weather, and privacy-sensitive settings where cameras and LiDAR often…
Scratched Lenses, Shifted Depth: Passive Camera-Side Optical Attacks
Qinlin He, Zeming Zhuang, Yongji Wu +3
Physical adversarial attacks on vision systems are typically studied via scene manipulation, such as adversarial patches or projections. A smaller body of work has examined camera-…
AdvScene: Rethinking Adversarial Patch Evaluation Through Scene Robustness
Xiaoyong, Yuan, Lan +1
Adversarial patches are physical patterns attached to real objects to mislead AI vision systems. Their real-world risk is not determined by a single successful prediction, but by w…
When AI Persuades: Adversarial Explanation Attacks on Human Trust in AI-Assisted Decision Making
Shutong Fan, Lan Zhang, Xiaoyong Yuan
Most adversarial threats in artificial intelligence (AI) target the computational behavior of models rather than the humans who rely on them. Yet modern AI systems increasingly ope…
MOBA: A Material-Oriented Backdoor Attack against LiDAR-based 3D Object Detection Systems
Saket S. Chaturvedi, Gaurav Bagwe, Lan Zhang +2
LiDAR-based 3D object detection is widely used in safety-critical systems. However, these systems remain vulnerable to backdoor attacks that embed hidden malicious behaviors during…
Your RAG is Unfair: Exposing Fairness Vulnerabilities in Retrieval-Augmented Generation via Backdoor Attacks
Gaurav Bagwe, Saket S. Chaturvedi, Xiaolong Ma +3
Retrieval-augmented generation (RAG) enhances factual grounding by integrating retrieval mechanisms with generative models but introduces new attack surfaces, particularly through…
Position: Human Factors Reshape Adversarial Analysis in Human-AI Decision-Making Systems
Shutong Fan, Lan Zhang, Xiaoyong Yuan
As Artificial Intelligence (AI) increasingly supports human decision-making, its vulnerability to adversarial attacks grows. However, the existing adversarial analysis predominantl…
DyME: Dynamic Multi-Concept Erasure in Diffusion Models with Bi-Level Orthogonal LoRA Adaptation
Jiaqi Liu, Lan Zhang, Xiaoyong Yuan
Text-to-image diffusion models (DMs) inadvertently reproduce copyrighted styles and protected visual concepts, raising legal and ethical concerns. Concept erasure has emerged as a…
AIP: Subverting Retrieval-Augmented Generation via Adversarial Instructional Prompt
Saket S. Chaturvedi, Gaurav Bagwe, Lan Zhang +1
Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by retrieving relevant documents from external sources to improve factual accuracy and verifiability. How…
Sample-Efficient Reinforcement Learning Controller for Deep Brain Stimulation in Parkinson's Disease
Harsh Ravivarapu, Gaurav Bagwe, Xiaoyong Yuan +2
Deep brain stimulation (DBS) is an established intervention for Parkinson's disease (PD), but conventional open-loop systems lack adaptability, are energy-inefficient due to contin…
You Don't Need All Attentions: Distributed Dynamic Fine-Tuning for Foundation Models
Shiwei Ding, Lan Zhang, Zhenlin Wang +2
Fine-tuning plays a crucial role in adapting models to downstream tasks with minimal training efforts. However, the rapidly increasing size of foundation models poses a daunting ch…
What Lurks Within? Concept Auditing for Shared Diffusion Models at Scale
Xiaoyong Yuan, Xiaolong Ma, Linke Guo +1
Diffusion models (DMs) have revolutionized text-to-image generation, enabling the creation of highly realistic and customized images from text prompts. With the rise of parameter-e…