1 citations · 1 across the 4 of their papers we have counts for
5 papers
Agentic-imodels: Evolving agentic interpretability tools via autoresearch
Chandan Singh, Yan Shuo Tan, Weijia Xu +4
Agentic data science (ADS) systems are rapidly improving their capability to autonomously analyze, fit, and interpret data, potentially moving towards a future where agents conduct…
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…
Do explanations generalize across large reasoning models?
Koyena Pal, David Bau, Chandan Singh
Large reasoning models (LRMs) produce a textual chain of thought (CoT) in the process of solving a problem, which serves as a potentially powerful tool to understand the problem by…
Human-AI Co-design for Clinical Prediction Models
Jean Feng, Avni Kothari, Patrick Vossler +6
Developing safe, effective, and practically useful clinical prediction models (CPMs) traditionally requires iterative collaboration between clinical experts, data scientists, and i…
Bayesian Concept Bottleneck Models with LLM Priors
Jean Feng, Avni Kothari, Luke Zier +2
Concept Bottleneck Models (CBMs) have been proposed as a compromise between white-box and black-box models, aiming to achieve interpretability without sacrificing accuracy. The sta…