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Zijian Zheng

2 accepted papers

2026

Graph-augmented and Over-smoothing-resistant Contrastive Clustering for Short Text

AAAI 2026technical

Short texts present significant challenges for clustering due to semantic sparsity, limited contextual information, and ambiguous category boundaries. While recent studies incorporating contrastive learning and cluster structure optimization have improved performance, their reliance on augmented sam

Cited by 0SourcePDFScholar
2025

FNSCC: Fuzzy Neighborhood-Aware Self-Supervised Contrastive Clustering for Short Text

EMNLP 2025

Short texts pose significant challenges for clustering due to semantic sparsity, limited context, and fuzzy category boundaries. Although recent contrastive learning methods improve instance-level representation, they often overlook local semantic structure within the clustering head. Moreover, trea