10 papers
Feedback Control for Multi-Objective Graph Self-Supervision
Karish Grover, Theodore Vasiloudis, Han Xie +3
Can multi-task self-supervised learning on graphs be coordinated without the usual tug-of-war between objectives? Graph self-supervised learning (SSL) offers a growing toolbox of p…
LAKEGEN: A LLM-based Tabular Corpus Generator for Evaluating Dataset Discovery in Data Lakes
Zhenwei Dai, Chuan Lei, Asterios Katsifodimos +3
How to generate a large, realistic set of tables along with joinability relationships, to stress-test dataset discovery methods? Dataset discovery methods aim to automatically iden…
Spectro-Riemannian Graph Neural Networks
Karish Grover, Haiyang Yu, Xiang Song +4
Can integrating spectral and curvature signals unlock new potential in graph representation learning? Non-Euclidean geometries, particularly Riemannian manifolds such as hyperbolic…
HybGRAG: Hybrid Retrieval-Augmented Generation on Textual and Relational Knowledge Bases
Meng-Chieh Lee, Qi Zhu, Costas Mavromatis +5
Given a semi-structured knowledge base (SKB), where text documents are interconnected by relations, how can we effectively retrieve relevant information to answer user questions? R…
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…
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…