Author

Yu-Su Wang

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Preprint Oct 2026

Looped GNNs Beyond Fixed Depth: Graph Size Generalization and Parameter-Efficient Adaptation

Generalizing from small graphs to larger ones can require computation beyond the depth of a neural model used during training. We study target tasks that admit a common local iterative computation and whose effective dependency radius grows with graph size. The central idea is to learn a local update rule through GNN p...

Zhi-Yang Wang, Zhi-Shang Luo, Yu-Su Wang · 0 citations

#machine learning Preprint Oct 2026

Algorithmically Aligned Neural Agglomerative Tree Construction

Linkage algorithms for hierarchical clustering (HC) are a powerful and efficient framework for constructing clustering trees, yet it is often unclear which merge rule best suits a given dataset or task. In contrast, neural approaches can learn from data, but often fail to retain the efficiency and size generalization o...

Robert R. Nerem, P. Singh, Cheyenne Ward et al. · 0 citations