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cs.LG2026
SleuthBench: Benchmarking Statistical LLM Evaluation Using Tabular Hidden Signals
Jingyun Jia, Antoine Remond-Tiedrez, Aaron Alvarez +3
Evaluating statistical discovery by large language model (LLM) agents requires verifiable analytical ground truth. Establishing such ground truth for real-world datasets is costly,…
cs.LG2026
Selecting Feature Interactions for Generalized Additive Models by Distilling Foundation Models
Jingyun Jia, Chandan Singh, Rich Caruana +1
Identifying meaningful feature interactions is a central challenge in building accurate and interpretable models for tabular data. Generalized additive models (GAMs) have shown gre…