Zhigang Liu — accepted AI-conference papers

2026

An Asymmetric Latent Factorization-of-Tensors Model for Relation Extraction

Weiling Li, Zhaoheng Shi, Jiajia Mi, Zhigang Liu, Jialiang Wang, Xin Luo

ICML 2026poster

Latent Factorization-of-Tensors (LFT) models are an effective approach for relation extraction. Existing LFT models assume each mode of the target tensor corresponds to a entity set and the relationships between entity sets are bipartite graphs to explore the relationships among entities within a mo…

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2025

A Relaxed Symmetric Non-negative Matrix Factorization Approach for Community Discovery (Extended Abstract)

Zhigang Liu, Hao Yan, Yurong Zhong, Weiling Li

IJCAI 2025

Community discovery is a prominent issue in com-plex network analysis. Symmetric non-negative matrix factorization (SNMF) is frequently adopted to tackle this issue. The use of a single feature matrix can depict network symmetry, but it limits its ability to learn node representations. To break this

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