3 citations · 4 across the 6 of their papers we have counts for
7 papers
Dataset Inference for Data Provenance and Privacy Auditing in Tabular Foundation Models
Dariush Wahdany, Jesse Cresswell, Naiqing Guan +3
Tabular foundation models (TFMs) are increasingly deployed through black-box APIs and trained on large collections of real-world tabular datasets. As this training paradigm becomes…
Relational Deep Dive: Error-Aware Queries Over Unstructured Data
Daren Chao, Kaiwen Chen, Naiqing Guan +1
Unstructured data is pervasive, but analytical queries demand structured representations, creating a significant extraction challenge. Existing methods like RAG lack schema awarene…
WeShap: Weak Supervision Source Evaluation with Shapley Values
Naiqing Guan, Nick Koudas
Efficient data annotation stands as a significant bottleneck in training contemporary machine learning models. The Programmatic Weak Supervision (PWS) pipeline presents a solution…
ActiveDP: Bridging Active Learning and Data Programming
Naiqing Guan, Nick Koudas
Modern machine learning models require large labelled datasets to achieve good performance, but manually labelling large datasets is expensive and time-consuming. The data programm…
Can Large Language Models Design Accurate Label Functions?
Naiqing Guan, Kaiwen Chen, Nick Koudas
Programmatic weak supervision methodologies facilitate the expedited labeling of extensive datasets through the use of label functions (LFs) that encapsulate heuristic data sources…
Estimating Regression Predictive Distributions with Sample Networks
Ali Harakeh, Jordan Hu, Naiqing Guan +2
Estimating the uncertainty in deep neural network predictions is crucial for many real-world applications. A common approach to model uncertainty is to choose a parametric distribu…
TENET: A Framework for Modeling Tensor Dataflow Based on Relation-centric Notation
Liqiang Lu, Naiqing Guan, Yuyue Wang +5
Accelerating tensor applications on spatial architectures provides high performance and energy-efficiency, but requires accurate performance models for evaluating various dataflow…