most citedEffect of Adapting to Human Preferences on Trust in Human-Robot Teaming

2 citations · 4 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CR20244 cited

DisDet: Exploring Detectability of Backdoor Attack on Diffusion Models

Yang Sui, Huy Phan, Jinqi Xiao +6

In the exciting generative AI era, the diffusion model has emerged as a very powerful and widely adopted content generation and editing tool for various data modalities, making the…

cs.RO20232 cited

Effect of Adapting to Human Preferences on Trust in Human-Robot Teaming

Shreyas Bhat, Joseph B. Lyons, Cong Shi +1

We present the effect of adapting to human preferences on trust in a human-robot teaming task. The team performs a task in which the robot acts as an action recommender to the huma…

cs.CV2023

Benchmarking and Analyzing Robust Point Cloud Recognition: Bag of Tricks for Defending Adversarial Examples

Qiufan Ji, Lin Wang, Cong Shi +3

Deep Neural Networks (DNNs) for 3D point cloud recognition are vulnerable to adversarial examples, threatening their practical deployment. Despite the many research endeavors have…

cs.RO20231 cited

Reward Shaping for Building Trustworthy Robots in Sequential Human-Robot Interaction

Yaohui Guo, X. Jessie Yang, Cong Shi

Trust-aware human-robot interaction (HRI) has received increasing research attention, as trust has been shown to be a crucial factor for effective HRI. Research in trust-aware HRI…

cs.CR2023

BarrierBypass: Out-of-Sight Clean Voice Command Injection Attacks through Physical Barriers

Payton Walker, Tianfang Zhang, Cong Shi +2

The growing adoption of voice-enabled devices (e.g., smart speakers), particularly in smart home environments, has introduced many security vulnerabilities that pose significant th…

cs.CR20221 cited

RIBAC: Towards Robust and Imperceptible Backdoor Attack against Compact DNN

Huy Phan, Cong Shi, Yi Xie +7

Recently backdoor attack has become an emerging threat to the security of deep neural network (DNN) models. To date, most of the existing studies focus on backdoor attack against t…