papers

Publications (21)

cs.HC2026

VisGuardian: A Lightweight Group-based Privacy Control Technique For Front Camera Data From AR Glasses in Home Environments

Shuning Zhang, Qucheng Zang, Yongquan `Owen' Hu +7

Always-on sensing of AI applications on AR glasses makes traditional permission techniques ill-suited for context-dependent visual data, especially within home environments. The ho…

eess.IV2026

Zero-shot Multi-Contrast Brain MRI Registration by Intensity Randomizing T1-weighted MRI (LUMIR25)

Hengjie Liu, Yimeng Dou, Di Xu +3

In this paper, we present our submission to the LUMIR25 task of Learn2Reg 2025, which ranked 1st overall on the test set. Extended from LUMIR24, this year's task focuses on zero-sh…

cs.HC2023

Decoding Fear: Exploring User Experiences in Virtual Reality Horror Games

He Zhang, Xinyang Li, Christine Qiu +1

This preliminary study investigated user experiences in VR horror games, highlighting fear-triggering and gender-based differences in perception. By utilizing a scientifically vali…

cs.HC2026

Roomify: Spatially-Grounded Style Transformation for Immersive Virtual Environments

Xueyang Wang, Qinxuan Cen, Weitao Bi +5

We present Roomify, a spatially-grounded transformation system that generates themed virtual environments anchored to users' physical rooms while maintaining spatial structure and…

cs.LG2023

Differentially Private Learning with Per-Sample Adaptive Clipping

Tianyu Xia, Shuheng Shen, Su Yao +4

Privacy in AI remains a topic that draws attention from researchers and the general public in recent years. As one way to implement privacy-preserving AI, differentially private le…

cs.CV2024

Clean-image Backdoor Attacks

Dazhong Rong, Guoyao Yu, Shuheng Shen +6

To gather a significant quantity of annotated training data for high-performance image classification models, numerous companies opt to enlist third-party providers to label their…

cs.CV2025

Zero-shot Emotion Annotation in Facial Images Using Large Multimodal Models: Benchmarking and Prospects for Multi-Class, Multi-Frame Approaches

He Zhang, Xinyi Fu

This study investigates the feasibility and performance of using large multimodal models (LMMs) to automatically annotate human emotions in everyday scenarios. We conducted experim…

cs.HC2024

VRMN-bD: A Multi-modal Natural Behavior Dataset of Immersive Human Fear Responses in VR Stand-up Interactive Games

He Zhang, Xinyang Li, Yuanxi Sun +3

Understanding and recognizing emotions are important and challenging issues in the metaverse era. Understanding, identifying, and predicting fear, which is one of the fundamental h…

cs.RO2026

Detecting Heel Strike and toe off Events Using Kinematic Methods and LSTM Models

Longbin Zhang, Zhizhang Li, Xinyi Fu +10

Accurate gait event detection is crucial for gait analysis, rehabilitation, and assistive technology, particularly in exoskeleton control, where precise identification of stance an…

cs.HC2023

Multi-channel Sensor Network Construction, Data Fusion and Challenges for Smart Home

He Zhang, Robin Ananda, Xinyi Fu +4

Both sensor networks and data fusion are essential foundations for developing the smart home Internet of Things (IoT) and related fields. We proposed a multi-channel sensor network…

cs.CL2026

DongYuan: An LLM-Based Framework for Integrative Chinese and Western Medicine Spleen-Stomach Disorders Diagnosis

Hua Li, Yingying Li, Xiaobin Feng +8

The clinical burden of spleen-stomach disorders is substantial. While large language models (LLMs) offer new potential for medical applications, they face three major challenges in…

cs.IR2024

Multi-Grained Preference Enhanced Transformer for Multi-Behavior Sequential Recommendation

Chuan He, Yongchao Liu, Qiang Li +5

Sequential recommendation (SR) aims to predict the next purchasing item according to users' dynamic preference learned from their historical user-item interactions. To improve the…

cs.CR2024

Protecting Split Learning by Potential Energy Loss

Fei Zheng, Chaochao Chen, Lingjuan Lyu +5

As a practical privacy-preserving learning method, split learning has drawn much attention in academia and industry. However, its security is constantly being questioned since the…

cs.HC2026

VR Calm Plus: Coupling a Squeezable Tangible Interaction with Immersive VR for Stress Regulation

He Zhang, Xinyang Li, Xingyu Zhou +1

While Virtual Reality (VR) is increasingly employed for stress management, most applications rely heavily on audio-visual stimuli and overlook the therapeutic potential of squeezin…

cs.HC2025

Body Management Information Practices on a Female-dominant Platform

Na Li, Chuhao Wu, Hongyang Zhou +5

With growing awareness of long-term health and wellness, everyday body management has become a widespread practice. Social media platforms and health-related applications offer abu…

cs.CV2024

PromptKD: Unsupervised Prompt Distillation for Vision-Language Models

Zheng Li, Xiang Li, Xinyi Fu +4

Prompt learning has emerged as a valuable technique in enhancing vision-language models (VLMs) such as CLIP for downstream tasks in specific domains. Existing work mainly focuses o…

cs.LG2023

Privacy-preserving design of graph neural networks with applications to vertical federated learning

Ruofan Wu, Mingyang Zhang, Lingjuan Lyu +6

The paradigm of vertical federated learning (VFL), where institutions collaboratively train machine learning models via combining each other's local feature or label information, h…

cs.CR2026

PromptShield Home: Ambient Multimodal Prompt Injection Defense for Smart-Home Agents

He Zhang, Feilong Li, Dingning Long +5

Smart-home assistants increasingly use multimodal large language models (MLLMs) that perceive video and audio directly. This raises a safety question specific to the home: can the…

cs.CR2025

I Can Tell Your Secrets: Inferring Privacy Attributes from Mini-app Interaction History in Super-apps

Yifeng Cai, Ziqi Zhang, Mengyu Yao +8

Super-apps have emerged as comprehensive platforms integrating various mini-apps to provide diverse services. While super-apps offer convenience and enriched functionality, they ca…

cs.CV2025

Augmenting Image Annotation: A Human-LMM Collaborative Framework for Efficient Object Selection and Label Generation

He Zhang, Xinyi Fu, John M. Carroll

Traditional image annotation tasks rely heavily on human effort for object selection and label assignment, making the process time-consuming and prone to decreased efficiency as an…

cs.RO2026

POIROT: Investigating Direct Tangible vs. Digitally Mediated Interaction and Attitude Moderation in Multi-party Murder Mystery Games

Wen Chen, Rongxi Chen, Shankai Chen +5

As social robots take on increasingly complex roles like game masters (GMs) in multi-party games, the expectation that physicality universally enhances user experience remains deba…