Publications (5)
I Don't Know You, But I Can Catch You: Real-Time Defense against Diverse Adversarial Patches for Object Detectors
Zijin Lin, Yue Zhao, Kai Chen +1
Deep neural networks (DNNs) have revolutionized the field of computer vision like object detection with their unparalleled performance. However, existing research has shown that DN…
LLM Factoscope: Uncovering LLMs' Factual Discernment through Inner States Analysis
Jinwen He, Yujia Gong, Kai Chen +3
Large Language Models (LLMs) have revolutionized various domains with extensive knowledge and creative capabilities. However, a critical issue with LLMs is their tendency to produc…
Medical Visual Prompting (MVP): A Unified Framework for Versatile and High-Quality Medical Image Segmentation
Yulin Chen, Guoheng Huang, Kai Huang +5
Accurate segmentation of lesion regions is crucial for clinical diagnosis and treatment across various diseases. While deep convolutional networks have achieved satisfactory result…
Hidden self-duality and exact mobility edges in quasiperiodic network models
Hai-Tao Hu, Xiaoshui Lin, Ai-Min Guo +3
In one-dimensional quasiperiodic systems, only a few models with exact mobility edges (MEs) have been constructed using generalized self-duality theory, Avila's global theory, or t…
PrivacyXray: Detecting Privacy Breaches in LLMs through Semantic Consistency and Probability Certainty
Jinwen He, Yiyang Lu, Zijin Lin +2
Large Language Models (LLMs) are widely used in sensitive domains, including healthcare, finance, and legal services, raising concerns about potential private information leaks dur…