9 papers
HELO-APR: Enhancing Low-Resource Program Repair through Cross-Lingual Knowledge Transfer
Zhipeng Wang, Boyang Yang, Yidong Wan +5
Large Language Models (LLMs) perform well on automatic program repair (APR) for high-resource programming languages (HRPLs), but their effectiveness drops sharply in low-resource p…
GS-Quant: Granular Semantic and Generative Structural Quantization for Knowledge Graph Completion
Qizhuo Xie, Yunhui Liu, Yu Xing +4
Large Language Models (LLMs) have shown immense potential in Knowledge Graph Completion (KGC), yet bridging the modality gap between continuous graph embeddings and discrete LLM to…
Beyond the Academic Monoculture: A Unified Framework and Industrial Perspective for Attributed Graph Clustering
Yunhui Liu, Yue Liu, Yongchao Liu +4
Attributed Graph Clustering (AGC) is a fundamental unsupervised task that partitions nodes into cohesive groups by jointly modeling structural topology and node attributes. While t…
Learning Hierarchical Knowledge in Text-Rich Networks with Taxonomy-Informed Representation Learning
Yunhui Liu, Yongchao Liu, Yinfeng Chen +3
Hierarchical knowledge structures are ubiquitous across real-world domains and play a vital role in organizing information from coarse to fine semantic levels. While such structure…
Mitigating Homophily Disparity in Graph Anomaly Detection: A Scalable and Adaptive Approach
Yunhui Liu, Qizhuo Xie, Yinfeng Chen +4
Graph anomaly detection (GAD) aims to identify nodes that deviate from normal patterns in structure or features. While recent GNN-based approaches have advanced this task, they str…
Bridging Academia and Industry: A Comprehensive Benchmark for Attributed Graph Clustering
Yunhui Liu, Pengyu Qiu, Yu Xing +6
Attributed Graph Clustering (AGC) is a fundamental unsupervised task that integrates structural topology and node attributes to uncover latent patterns in graph-structured data. De…