Author

Huizhe Zhang

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Jul 2026

Grad2Fair: A Gradient-driven Approach for Graph Fairness without Demographics

This work investigates the problem of graph fairness without demographic information and proposes Grad2Fair, a gradient-guided approach for group fairness without demographics that directly leverages gradients to debias and eliminates demographic prediction, thereby enabling stable fairness performance.

Yuchang Zhu, Ze-Zhong Xie, Huizhe Zhang et al. · arXiv.org · 0 citations

Preprint Jul 2026

Scalable and Efficient Joint Spiking Embedding Predictive Architecture for Large-Scale Dynamic Graphs

SG-JEPA is proposed, a joint spiking embedding predictive architecture for large-scale dynamic graphs that avoids the complex machinery (negative sampling, graph augmentations, edge-level reconstruction, etc.), resulting in superior training efficiency and memory scalability compared with prior self-supervised dynamic...

Huizhe Zhang, Yuchang Zhu, Huazhen Zhong et al. · 0 citations