5 papers
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…
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…
"Privacy across the boundary": Examining Perceived Privacy Risk Across Data Transmission and Sharing Ranges of Smart Home Personal Assistants
Shuning Zhang, Shixuan Li, Haobin Xing +4
As Smart Home Personal Assistants (SPAs) evolve into social agents, understanding user privacy necessitates interpersonal communication frameworks, such as Privacy Boundary Theory…
Differentiable Semantic Meta-Learning Framework for Long-Tail Motion Forecasting in Autonomous Driving
Bin Rao, Chengyue Wang, Haicheng Liao +7
Long-tail motion forecasting is a core challenge for autonomous driving, where rare yet safety-critical events-such as abrupt maneuvers and dense multi-agent interactions-dominate…
CoT-Drive: Efficient Motion Forecasting for Autonomous Driving with LLMs and Chain-of-Thought Prompting
Haicheng Liao, Hanlin Kong, Bonan Wang +5
Accurate motion forecasting is crucial for safe autonomous driving (AD). This study proposes CoT-Drive, a novel approach that enhances motion forecasting by leveraging large langua…