1 citations · 1 across the 8 of their papers we have counts for
9 papers
Peer review should constrain evaluative authority
Hanrui Wang, Timo Spinde, Isabella Habereder +2
Our position shifts the target of peer-review reform from reducing uncertainty through evaluator improvement or judgment aggregation to constraining evaluative authority under pers…
Shared Vulnerabilities in Robustness-Optimized Defenses: One Breach Exposes the Family
Hanrui Wang, Ruihao Zheng, Shuo Wang +3
Adversarial robustness optimization aims to preserve correct prediction under adversarial perturbations, and has produced substantial robustness gains through methods such as adver…
Role-Aware Artificial Intelligence Across Augmentation and Automation in Human-Machine Symbiosis
Ching-Chun Chang, Yuchen Guo, Hanrui Wang +2
The evolution of artificial intelligence (AI) has rendered the boundary between humanity and computational machinery increasingly ambiguous. In the presence of more interwoven rela…
GFT-GCN: Privacy-Preserving 3D Face Mesh Recognition with Spectral Diffusion
Hichem Felouat, Hanrui Wang, Isao Echizen
3D face recognition offers a robust biometric solution by capturing facial geometry, providing resilience to variations in illumination, pose changes, and presentation attacks. Its…
DiffMI: Breaking Face Recognition Privacy via Diffusion-Driven Training-Free Model Inversion
Hanrui Wang, Shuo Wang, Chun-Shien Lu +1
Face recognition poses serious privacy risks due to its reliance on sensitive and immutable biometric data. While modern systems mitigate privacy risks by mapping facial images to…
Imitation Game for Adversarial Disillusion with Chain-of-Thought Reasoning in Generative AI
Ching-Chun Chang, Fan-Yun Chen, Shih-Hong Gu +3
As the cornerstone of artificial intelligence, machine perception confronts a fundamental threat posed by adversarial illusions. These adversarial attacks manifest in two primary f…
GreedyPixel: Fine-Grained Black-Box Adversarial Attack Via Greedy Algorithm
Hanrui Wang, Ching-Chun Chang, Chun-Shien Lu +2
Deep neural networks are highly vulnerable to adversarial examples, which are inputs with small, carefully crafted perturbations that cause misclassification -- making adversarial…
Agentic Copyright Watermarking against Adversarial Evidence Forgery with Purification-Agnostic Curriculum Proxy Learning
Erjin Bao, Ching-Chun Chang, Hanrui Wang +1
With the proliferation of AI agents in various domains, protecting the ownership of AI models has become crucial due to the significant investment in their development. Unauthorize…
Minimal Cascade Gradient Smoothing for Fast Transferable Preemptive Adversarial Defense
Hanrui Wang, Ching-Chun Chang, Chun-Shien Lu +3
Adversarial attacks persist as a major challenge in deep learning. While training- and test-time defenses are well-studied, they often reduce clean accuracy, incur high cost, or fa…