9 papers
Semi-Supervised Text-Attributed Graph Distillation
Yurui Lai, Samir Moustafa, Renchi Yang +1
{\em Text-Attributed Graphs} (TAGs) have emerged as an expressive data model for integrating graph topology with rich textual semantics. Existing representation learning methods ov…
Adaptive Graph Refinement and Label Propagation with LLMs for Cost-Effective Entity Resolution
Hongtao Wang, Renchi Yang, Haoran Zheng +1
Dirty entity resolution (ER), which identifies records referring to the same real-world entity from a single, messy dataset, is a fundamental task in data management and mining. Ho…
Cross-Contrastive Clustering for Multimodal Attributed Graphs with Dual Graph Filtering
Haoran Zheng, Renchi Yang, Hongtao Wang +1
Multimodal Attributed Graphs (MMAGs) are an expressive data model for representing the complex interconnections among entities that associate attributes from multiple data modaliti…
Rethinking Message Passing Neural Networks with Diffusion Distance-guided Stress Majorization
Haoran Zheng, Renchi Yang, Yubo Zhou +1
Message passing neural networks (MPNNs) have emerged as go-to models for learning on graph-structured data in the past decade. Despite their effectiveness, most of such models stil…
Rethinking Semi-Supervised Node Classification with Self-Supervised Graph Clustering
Songbo Wang, Renchi Yang, Yurui Lai +2
The emergence of graph neural networks (GNNs) has offered a powerful tool for semi-supervised node classification tasks. Subsequent studies have achieved further improvements throu…
Empowering Graph-based Approximate Nearest Neighbor Search with Adaptive Awareness Capabilities
Jiancheng Ruan, Tingyang Chen, Renchi Yang +2
Approximate Nearest Neighbor Search (ANNS) in high-dimensional spaces finds extensive applications in databases, information retrieval, recommender systems, etc. While graph-based…
Simple yet Effective Graph Distillation via Clustering
Yurui Lai, Taiyan Zhang, Renchi Yang
Despite plentiful successes achieved by graph representation learning in various domains, the training of graph neural networks (GNNs) still remains tenaciously challenging due to…
Cequel: Cost-Effective Querying of Large Language Models for Text Clustering
Hongtao Wang, Taiyan Zhang, Renchi Yang +1
Text clustering aims to automatically partition a collection of documents into coherent groups based on their linguistic features. In the literature, this task is formulated either…
Leveraging Large Language Models for Effective Label-free Node Classification in Text-Attributed Graphs
Taiyan Zhang, Renchi Yang, Yurui Lai +3
Graph neural networks (GNNs) have become the preferred models for node classification in graph data due to their robust capabilities in integrating graph structures and attributes.…