Yebin Lim

Multi-level Diagnosis and Evaluation for Robust Tabular Feature Engineering with Large Language Models

Recent advancements in large language models (LLMs) have shown promise in feature engineering for tabular data, but concerns about their reliability persist, especially due to variability in generated outputs. We introduce a multi-level diagnosis and evaluation framework to assess the robustness of