Author

Si-An Chen

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Preprint Sep 2026

Rethinking One-Shot Federated Graph Learning: Training-Free Statistical Estimation

SPEAR (Statistical Prototype Estimation with Adaptive Reliability), a completely training-free framework that directly computes topology-smoothed class prototypes from local graphs in the original feature space, suggests that training-free statistical estimation, rather than local GNN optimization, provides the key to...

Shu-Tong Zheng, Si-An Chen · 0 citations

#natural language process... Preprint Sep 2026

Signed Rescue Routing: Harm-Aware Cascades for Efficient LLM Inference

Signed Rescue Routing is introduced, a budgeted routing method that predicts these two events separately and ranks requests by their difference and shows that predicting incremental value, rather than model uncertainty, is a simple and effective objective for efficient LLM cascades.

Zhe-Yuan Wang, Si-Yu Li, Pei-Qiao Song et al. · 1 citation

#machine learning Preprint Sep 2026

Rethinking One-Shot Federated Graph Learning: Training-Free Statistical Estimation

One-shot federated graph learning generally aims to train Graph Neural Networks (GNNs) across clients with disconnected subgraphs in a single communication round. Existing methods predominantly design advanced optimization strategies under the premise that local GNN training is indispensable. However, empirical observa...

Shu-Tong Zheng, Si-An Chen · 0 citations