23 citations · 56 across the 15 of their papers we have counts for
6 papers · 1 filter
Hierarchical Compression of Text-Rich Graphs via Large Language Models
Shichang Zhang, Da Zheng, Jiani Zhang +6
Text-rich graphs, prevalent in data mining contexts like e-commerce and academic graphs, consist of nodes with textual features linked by various relations. Traditional graph machi…
FeatNavigator: Automatic Feature Augmentation on Tabular Data
Jiaming Liang, Chuan Lei, Xiao Qin +4
Data-centric AI focuses on understanding and utilizing high-quality, relevant data in training machine learning (ML) models, thereby increasing the likelihood of producing accurate…
KGExplainer: Towards Exploring Connected Subgraph Explanations for Knowledge Graph Completion
Tengfei Ma, Xiang song, Wen Tao +6
Knowledge graph completion (KGC) aims to alleviate the inherent incompleteness of knowledge graphs (KGs), which is a critical task for various applications, such as recommendations…
OmniMatch: Effective Self-Supervised Any-Join Discovery in Tabular Data Repositories
Christos Koutras, Jiani Zhang, Xiao Qin +5
How can we discover join relationships among columns of tabular data in a data repository? Can this be done effectively when metadata is missing? Traditional column matching works…
Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey
Xi Fang, Weijie Xu, Fiona Anting Tan +7
Recent breakthroughs in large language modeling have facilitated rigorous exploration of their application in diverse tasks related to tabular data modeling, such as prediction, ta…
OpenTab: Advancing Large Language Models as Open-domain Table Reasoners
Kezhi Kong, Jiani Zhang, Zhengyuan Shen +5
Large Language Models (LLMs) trained on large volumes of data excel at various natural language tasks, but they cannot handle tasks requiring knowledge that has not been trained on…