23 citations · 56 across the 15 of their papers we have counts for
5 papers · 1 filter
Which Examples to Annotate for In-Context Learning? Towards Effective and Efficient Selection
Costas Mavromatis, Balasubramaniam Srinivasan, Zhengyuan Shen +4
Large Language Models (LLMs) can adapt to new tasks via in-context learning (ICL). ICL is efficient as it does not require any parameter updates to the trained LLM, but only few an…
NameGuess: Column Name Expansion for Tabular Data
Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan +3
Recent advances in large language models have revolutionized many sectors, including the database industry. One common challenge when dealing with large volumes of tabular data is…
Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space
Hengrui Zhang, Jiani Zhang, Balasubramaniam Srinivasan +5
Recent advances in tabular data generation have greatly enhanced synthetic data quality. However, extending diffusion models to tabular data is challenging due to the intricately v…
PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction
Shichang Zhang, Jiani Zhang, Xiang Song +4
Transparency and accountability have become major concerns for black-box machine learning (ML) models. Proper explanations for the model behavior increase model transparency and he…
OrthoReg: Improving Graph-regularized MLPs via Orthogonality Regularization
Hengrui Zhang, Shen Wang, Vassilis N. Ioannidis +7
Graph Neural Networks (GNNs) are currently dominating in modeling graph-structure data, while their high reliance on graph structure for inference significantly impedes them from w…