4 papers
Learning How Much to Think: Difficulty-Aware Dynamic MoEs for Graph Node Classification
Jiajun Zhou, Yadong Li, Xuanze Chen +4
Mixture-of-Experts (MoE) architectures offer a scalable path for Graph Neural Networks (GNNs) in node classification tasks but typically rely on static and rigid routing strategies…
RealHD: A High-Quality Dataset for Robust Detection of State-of-the-Art AI-Generated Images
Hanzhe Yu, Yun Ye, Jintao Rong +2
The rapid advancement of generative AI has raised concerns about the authenticity of digital images, as highly realistic fake images can now be generated at low cost, potentially i…
Improving the Convergence Rate of Ray Search Optimization for Query-Efficient Hard-Label Attacks
Xinjie Xu, Shuyu Cheng, Dongwei Xu +2
In hard-label black-box adversarial attacks, where only the top-1 predicted label is accessible, the prohibitive query complexity poses a major obstacle to practical deployment. In…
Boosting Ray Search Procedure of Hard-label Attacks with Transfer-based Priors
Chen Ma, Xinjie Xu, Shuyu Cheng +1
One of the most practical and challenging types of black-box adversarial attacks is the hard-label attack, where only the top-1 predicted label is available. One effective approach…