4 papers
Assessing LLMs for Serendipity Discovery in Knowledge Graphs: A Case for Drug Repurposing
Mengying Wang, Chenhui Ma, Ao Jiao +6
Large Language Models (LLMs) have greatly advanced knowledge graph question answering (KGQA), yet existing systems are typically optimized for returning highly relevant but predict…
ML-Asset Management: Curation, Discovery, and Utilization
Mengying Wang, Moming Duan, Yicong Huang +3
Machine learning (ML) assets, such as models, datasets, and metadata, are central to modern ML workflows. Despite their explosive growth in practice, these assets are often underut…
Inference-friendly Graph Compression for Graph Neural Networks
Yangxin Fan, Haolai Che, Yinghui Wu
Graph Neural Networks (GNNs) have demonstrated promising performance in graph analysis. Nevertheless, the inference process of GNNs remains costly, hindering their applications for…
Generating Skyline Datasets for Data Science Models
Mengying Wang, Hanchao Ma, Yiyang Bian +2
Preparing high-quality datasets required by various data-driven AI and machine learning models has become a cornerstone task in data-driven analysis. Conventional data discovery me…