18 citations · 20 across the 11 of their papers we have counts for
4 papers · 1 filter
C2PO: Diagnosing and Disentangling Bias Shortcuts in LLMs
Xuan Feng, Bo An, Tianlong Gu +4
Bias in Large Language Models (LLMs) poses significant risks to trustworthiness, manifesting primarily as stereotypical biases (e.g., gender or racial stereotypes) and structural b…
CLIP-FTI: Fine-Grained Face Template Inversion via CLIP-Driven Attribute Conditioning
Longchen Dai, Zixuan Shen, Zhiheng Zhou +2
Face recognition systems store face templates for efficient matching. Once leaked, these templates pose a threat: inverting them can yield photorealistic surrogates that compromise…
Fine-Grained DINO Tuning with Dual Supervision for Face Forgery Detection
Tianxiang Zhang, Peipeng Yu, Zhihua Xia +3
The proliferation of sophisticated deepfakes poses significant threats to information integrity. While DINOv2 shows promise for detection, existing fine-tuning approaches treat it…
Unlocking the Capabilities of Large Vision-Language Models for Generalizable and Explainable Deepfake Detection
Peipeng Yu, Jianwei Fei, Hui Gao +3
Current Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities in understanding multimodal data, but their potential remains underexplored for deepfake dete…