1 citations · 2 across the 17 of their papers we have counts for
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Understanding Security and Privacy Perceptions of Content Creators Regarding AI Labels of AI-Generated Content
Shuning Zhang, Hui Wang, Rongjun Ma +4
AI labels, typically implemented via underlying tracing mechanisms such as watermarks and metadata, are crucial for protecting Artificial Intelligence-Generated Content (AIGC) agai…
Is It Real? Exploiting Virtual-Physical Discrimination Vulnerability in Mixed Reality
Xueyang Wang, Xihuan Yao, Yanming Xiu +3
Consumer mixed reality (MR) headsets seamlessly blend virtual content into physical environments with sufficient fidelity that users may be unable to distinguish virtual objects fr…
CANote: Empowering Fact-checking Note Writing Through Scaffolded and Provenance-based Human-AI Collaboration
Shuning Zhang, Jingruo Chen, Yuwei Chuai +4
Crowdsourced fact-checking mechanisms, such as X's Community Notes, play a critical role in mitigating the spread of misinformation. However, drafting high-quality, evidence-based…
Investigating Novice Researchers' Perceptions of Research Privacy Within LLM-Assisted Workflows
Shuning Zhang, Changxi Wen, Eve He +4
Large Language Model (LLMs)-assisted scholarly workflows introduce critical privacy and intellectual property risks. As a uniquely vulnerable cohort driven by publication pressure…
Focused on the User, Overlooking the Risks: Security and Privacy Understandings, Practices and Challenges of Independent Chinese AI Agent Developers
Shuning Zhang, Mingyao Xu, Zhixin Huang +6
The proliferation of AI agents empowers independent developers, defined as individual or small groups who self-initiate projects rather than fulfill client-based contracts, to crea…
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…