collaborators

8 papers

cs.CV2026

AgentFoX: LLM Agent-Guided Fusion with eXplainability for AI-Generated Image Detection

Yangxin Yu, Yue Zhou, Bin Li +4

The realism of AI-generated images (AIGI) poses increasing challenges for reliable forensic detection, where heterogeneous expert detectors may produce conflicting predictions acro…

cs.CL2026

What Do LLMs Know About Alzheimer's Disease? Multi-loss Fine-Tuning and Probing for AD Detection

Lei Jiang, Yue Zhou, Natalie Parde

Reliable early detection of Alzheimer's disease (AD) is challenging, particularly due to the limited availability of labeled data. While large language models (LLMs) have shown str…

cs.CV2026

Simplicity Prevails: The Emergence of Generalizable AIGI Detection in Visual Foundation Models

Yue Zhou, Xinan He, Kaiqing Lin +3

While specialized detectors for AI-Generated Images (AIGI) achieve near-perfect accuracy on curated benchmarks, they suffer from a dramatic performance collapse in realistic, in-th…

cs.CV2026

MPF-Net: Exposing High-Fidelity AI-Generated Video Forgeries via Hierarchical Manifold Deviation and Micro-Temporal Fluctuations

Xinan He, Kaiqing Lin, Yue Zhou +8

With the rapid advancement of video generation models such as Veo and Wan, the visual quality of synthetic content has reached a level where macro-level semantic errors and tempora…

cs.CV2025

Guard Me If You Know Me: Protecting Specific Face-Identity from Deepfakes

Kaiqing Lin, Zhiyuan Yan, Ke-Yue Zhang +7

Securing personal identity against deepfake attacks is increasingly critical in the digital age, especially for celebrities and political figures whose faces are easily accessible…

cs.CV2025

Brought a Gun to a Knife Fight: Modern VFM Baselines Outgun Specialized Detectors on In-the-Wild AI Image Detection

Yue Zhou, Xinan He, Kaiqing Lin +4

While specialized detectors for AI-generated images excel on curated benchmarks, they fail catastrophically in real-world scenarios, as evidenced by their critically high false-neg…