Kate Lin — accepted AI-conference papers

2025

RADAR: Benchmarking Language Models on Imperfect Tabular Data

Ken Gu, Zhihan Zhang, Kate Lin, Yuwei Zhang, Akshay Paruchuri, Hong Yu +14

NeurIPS 2025poster

Language models (LMs) are increasingly being deployed to perform autonomous data analyses. However, their data awareness—the ability to recognize, reason over, and appropriately handle data artifacts such as missing values, outliers, and logical inconsistencies—remains underexplored. These artifacts…

Cited by 0 Source ↗code ↗Scholar ↗

2021

Automatic structured variational inference

Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore +1

AISTATS 2021poster

Stochastic variational inference offers an attractive option as a default method for differentiable probabilistic programming. However, the performance of the variational approach depends on the choice of an appropriate variational family. Here, we introduce automatic structured variational inferenc…

Cited by 37 Source ↗PDF ↗code ↗Scholar ↗