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20232026
most citedT2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models

2 citations · 4 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2026

Towards Robust Content Watermarking Against Removal and Forgery Attacks

Yifan Zhu, Yihan Wang, Xiao-Shan Gao

Generated contents have raised serious concerns about copyright protection, image provenance, and credit attribution. A potential solution for these problems is watermarking. Recen…

cs.CR2025

Provable Watermarking for Data Poisoning Attacks

Yifan Zhu, Lijia Yu, Xiao-Shan Gao

In recent years, data poisoning attacks have been increasingly designed to appear harmless and even beneficial, often with the intention of verifying dataset ownership or safeguard…

cs.LG2025

Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization

Shuang Liu, Yihan Wang, Yifan Zhu +2

Wasserstein distributionally robust optimization (WDRO) optimizes against worst-case distributional shifts within a specified uncertainty set, leading to enhanced generalization on…

cs.LG2025

Generalizability of Neural Networks Minimizing Empirical Risk Based on Expressive Ability

Lijia Yu, Yibo Miao, Yifan Zhu +2

The primary objective of learning methods is generalization. Classic uniform generalization bounds, which rely on VC-dimension or Rademacher complexity, fail to explain the signifi…

cs.LG2024★ 1 cited

PowerMLP: An Efficient Version of KAN

Ruichen Qiu, Yibo Miao, Shiwen Wang +3

The Kolmogorov-Arnold Network (KAN) is a new network architecture known for its high accuracy in several tasks such as function fitting and PDE solving. The superior expressive cap…

cs.CV2024★ 2 cited

T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models

Yibo Miao, Yifan Zhu, Yinpeng Dong +3

The recent development of Sora leads to a new era in text-to-video (T2V) generation. Along with this comes the rising concern about its security risks. The generated videos may con…

cs.CR2024

Toward Availability Attacks in 3D Point Clouds

Yifan Zhu, Yibo Miao, Yinpeng Dong +1

Despite the great progress of 3D vision, data privacy and security issues in 3D deep learning are not explored systematically. In the domain of 2D images, many availability attacks…

cs.LG2024

Efficient Availability Attacks against Supervised and Contrastive Learning Simultaneously

Yihan Wang, Yifan Zhu, Xiao-Shan Gao

Availability attacks can prevent the unauthorized use of private data and commercial datasets by generating imperceptible noise and making unlearnable examples before release. Idea…

cs.LG2023★ 1 cited

Detection and Defense of Unlearnable Examples

Yifan Zhu, Lijia Yu, Xiao-Shan Gao

Privacy preserving has become increasingly critical with the emergence of social media. Unlearnable examples have been proposed to avoid leaking personal information on the Interne…