Author

Yi-Jiang Li

2 papers indexed here

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#artificial intelligence May 2026

Scalable Heterogeneous Graph Foundation Models for Data-Driven Optimal Power Flow in Smart Grids

A large-scale heterogeneous graph-learning workflow, built on HydraGNN, for data-driven OPF surrogate modeling and graph foundation-model (GFM) development and shows that partial fine-tuning provides the strongest balance between predictive performance and computational requirements.

Massimiliano Lupo Pasini, Yi-Jiang Li, Kibaek Kim et al. · arXiv.org · 2 citations

#artificial intelligence May 2026

Attention Sinks and Outliers in Attention Residuals

OASIS is proposed, an outlier- and sink-aware method that stabilizes dual-normalized attention-residual architectures through explicit null routing and token-to-depth null coupling and offers insight into the low-bit sensitivity observed in AttnResidual.

Haozheng Luo, Hao-Ran Dai, Shao-Ling Zhang et al. · arXiv.org · 2 citations