Author

Jianru Shen

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Preprint Aug 2026

When Edge Importance Disagrees: Resistance-Ranked versus Betweenness Pruning on Urban Road Networks

Sparsifying large road-network graphs by removing a fraction of their edges is a common way to reduce storage and accelerate spatial queries, but the choice of which edges to remove can quietly degrade the network that remains. We compare three edge-importance criteria for deciding what to prune, namely uniform random...

Jian-Ru Shen · 0 citations

#machine learning Preprint Sep 2026

A Spectral Theory of Distortion in LLM Graph Reconstruction: Sharp Bounds and Empirical Characterization

Evaluations of graph reconstruction by language models typically report a single aggregate distance between the original and the reconstructed graph. We prove that for the Wasserstein distance between Laplacian spectra such a summary is bracketed by two edge counts, the net change in edge number from below and the symm...

Jian-Ru Shen · 0 citations

#machine learning Preprint Aug 2026

TailSpec-EASE: Knowledge-Graph-Regularized Linear Recommendation for Web Long-Tail Discovery

Recommender systems on Web platforms tend to over-serve popular items and neglect the long tail. Item-side knowledge graphs (KGs), often available as linked data or RDF-style Web resources, can help by connecting sparse items through shared semantic attributes. Many competitive KG-aware recommenders rely on graph neura...

Jian-Ru Shen · 0 citations

Preprint Aug 2026

TopoBudget: Persistent-Connectivity-Preserving Web Graph Sparsification for Reusable Community Analytics

TopoBudget couples exact multiscale connectivity with budgeted, reusable community preservation, and proves exact preservation of the component partition at every threshold, and that the conditioned objective is monotone and submodular, so greedy attains a (1-1/e) guarantee for the fixed-backbone residual problem.

Jian-Ru Shen · 0 citations