2 citations · 4 across the 13 of their papers we have counts for
6 papers · 1 filter
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…
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…
Pave Your Own Path: Graph Gradual Domain Adaptation on Fused Gromov-Wasserstein Geodesics
Zhichen Zeng, Ruizhong Qiu, Wenxuan Bao +6
Graph neural networks, despite their impressive performance, are highly vulnerable to distribution shifts on graphs. Existing graph domain adaptation (graph DA) methods often impli…
TransNet: Transfer Knowledge for Few-shot Knowledge Graph Completion
Lihui Liu, Zihao Wang, Dawei Zhou +6
Knowledge graphs (KGs) are ubiquitous and widely used in various applications. However, most real-world knowledge graphs are incomplete, which significantly degrades their performa…
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…
THeGCN: Temporal Heterophilic Graph Convolutional Network
Yuchen Yan, Yuzhong Chen, Huiyuan Chen +6
Graph Neural Networks (GNNs) have exhibited remarkable efficacy in diverse graph learning tasks, particularly on static homophilic graphs. Recent attention has pivoted towards more…