5 papers
Scalable Optimal Transport Algorithm for Network Alignment
Elaheh Hassani, Durga Mandarapu, Qi Yu +2
Network alignment identifies node correspondences across different networks and is a fundamental primitive in many data science applications, including social network analysis, fra…
DIB-OD: Preserving the Invariant Core for Robust Heterogeneous Graph Adaptation via Decoupled Information Bottleneck and Online Distillation
Yang Yan, Yunxuan Li, Qiuyan Wang +3
Graph pre-training can facilitate knowledge transfer across graph datasets, but severe structural and feature shifts may cause negative transfer and adaptation-induced overwriting…
PLANETALIGN: A Comprehensive Python Library for Benchmarking Network Alignment
Qi Yu, Zhichen Zeng, Yuchen Yan +5
Network alignment (NA) aims to identify node correspondence across different networks and serves as a critical cornerstone behind various downstream multi-network learning tasks. D…
Harnessing Consistency for Robust Test-Time LLM Ensemble
Zhichen Zeng, Qi Yu, Xiao Lin +6
Different large language models (LLMs) exhibit diverse strengths and weaknesses, and LLM ensemble serves as a promising approach to integrate their complementary capabilities. Desp…
Joint Optimal Transport and Embedding for Network Alignment
Qi Yu, Zhichen Zeng, Yuchen Yan +3
Network alignment, which aims to find node correspondence across different networks, is the cornerstone of various downstream multi-network and Web mining tasks. Most of the embedd…