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20242026
most citedWhen AI Persuades: Adversarial Explanation Attacks on Human Trust in AI-Assisted Decision Making

1 citations · 1 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2026

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-…

cs.CR2026

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…

cs.CR2026

Secure Semantic Communications via AI Defenses: Fundamentals, Solutions, and Future Directions

Lan Zhang, Chengsi Liang, Zeming Zhuang +4

Semantic communication (SemCom) redefines wireless communication from reproducing symbols to transmitting task-relevant semantics. However, this AI-native architecture also introdu…

cs.AI2026★ 1 cited

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…

cs.CR2025

Who's Wearing? Ear Canal Biometric Key Extraction for User Authentication on Wireless Earbuds

Chenpei Huang, Lingfeng Yao, Hui Zhong +5

Ear canal scanning/sensing (ECS) has emerged as a novel biometric authentication method for mobile devices paired with wireless earbuds. Existing studies have demonstrated the uniq…

cs.IR2025

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…

cs.HC2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.LG2025

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…

cs.LG2025

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…

cs.IT2024

Improving Channel Resilience for Task-Oriented Semantic Communications: A Unified Information Bottleneck Approach

Shuai Lyu, Yao Sun, Linke Guo +4

Task-oriented semantic communications (TSC) enhance radio resource efficiency by transmitting task-relevant semantic information. However, current research often overlooks the inhe…