1 citations · 1 across the 6 of their papers we have counts for
8 papers
Security of World-Model-Based Embodied AI: A Lifecycle of Threats, Defenses, and Evaluation
Fazhong Liu, Zhuoyan Chen, Haozhen Tan +3
World models give embodied AI a predictive core: they compress observations into states, simulate action-conditioned futures, and enable planning beyond reactive control. This pred…
DIPBox: A Multi-scale Testing Framework for Tracking Dataset Regeneration
Tian Dong, Yan Meng, Shaofeng Li +5
Training datasets have tremendous proprietary value and are vulnerable to unauthorized copying. Existing defenses mainly focus on tracking individual data points, but pay little at…
Trojan's Whisper: Stealthy Manipulation of OpenClaw through Injected Bootstrapped Guidance
Fazhong Liu, Zhuoyan Chen, Tu Lan +6
Autonomous coding agents are increasingly integrated into software development workflows, offering capabilities that extend beyond code suggestion to active system interaction and…
SlowBA: An efficiency backdoor attack towards VLM-based GUI agents
Junxian Li, Tu Lan, Haozhen Tan +2
Modern vision-language-model (VLM) based graphical user interface (GUI) agents are expected not only to execute actions accurately but also to respond to user instructions with low…
Depth Gives a False Sense of Privacy: LLM Internal States Inversion
Tian Dong, Yan Meng, Shaofeng Li +3
Large Language Models (LLMs) are increasingly integrated into daily routines, yet they raise significant privacy and safety concerns. Recent research proposes collaborative inferen…
Step-wise Adaptive Integration of Supervised Fine-tuning and Reinforcement Learning for Task-Specific LLMs
Jack Chen, Fazhong Liu, Naruto Liu +7
Large language models (LLMs) excel at mathematical reasoning and logical problem-solving. The current popular training paradigms primarily use supervised fine-tuning (SFT) and rein…
Model Inversion in Split Learning for Personalized LLMs: New Insights from Information Bottleneck Theory
Yunmeng Shu, Shaofeng Li, Tian Dong +2
Personalized Large Language Models (LLMs) have become increasingly prevalent, showcasing the impressive capabilities of models like GPT-4. This trend has also catalyzed extensive r…
VPVet: Vetting Privacy Policies of Virtual Reality Apps
Yuxia Zhan, Yan Meng, Lu Zhou +6
Virtual reality (VR) apps can harvest a wider range of user data than web/mobile apps running on personal computers or smartphones. Existing law and privacy regulations emphasize t…