Zhikui Chen

A Semantic Feasibility-Constrained NLI Framework for Scientific Relation Extraction

Scientific relation extraction aims to identify fine-grained semantic relations between domain-specific entities in scientific documents. However, complex scientific expressions, domain adaptation challenges, and subtle relation distinctions make this task difficult. To address these challenges, we propose a novel natu...

Multi-View Fair Clustering Guided by Cross-View Sensitive Information Discrepancy

Multi-view clustering (MVC) aims to uncover latent cluster structures by exploiting complementary information from multiple views. Despite substantial progress in clustering performance, fairness remains an important concern when MVC is applied to socially sensitive scenarios. Recent fair multi-view clustering methods...

Single-phase incomplete multi-view clustering via joint anchor refactoring and tensorial bipartite graph learning.

The inherent incompleteness of multi-view data poses significant challenges for conventional clustering methods, particularly those based on bipartite graph construction. Although existing approaches have made notable progress by refining graph architecture, they often overlook the critical role of anchor quality in de...

Decomposed tensorized graph learning with representation-induced view recovery for federated incomplete multi-view clustering