activity
20242026
most citedOpenAI GPT-5 System Card

17 citations · 17 across the 4 of their papers we have counts for

collaborators

6 papers

math.ST2026

Seeing the Forest for the Trees: The Gaussian Process Limit of BART

Cory McCartan, Melody Huang

Bayesian Additive Regression Trees (BART) have shown state-of-the-art performance in both prediction and causal inference problems. Previous theoretical work has attempted to expla…

cs.CL202617 cited

OpenAI GPT-5 System Card

Aaditya Singh, Adam Fry, Adam Perelman +483

This is the system card published alongside the OpenAI GPT-5 launch, August 2025. GPT-5 is a unified system with a smart and fast model that answers most questions, a deeper reason…

stat.ME2026

Relative Bias Under Imperfect Identification in Observational Causal Inference

Melody Huang, Cory McCartan

To conduct causal inference in observational settings, researchers must rely on certain identifying assumptions. In practice, these assumptions are unlikely to hold exactly. This p…

stat.AP2026

Estimating Consensus Ideal Points Using Multi-Source Data

Mellissa Meisels, Melody Huang, Tiffany M. Tang

In the advent of big data and machine learning, researchers now have a wealth of congressional candidate ideal point estimates at their disposal for theory testing. Weak relationsh…

stat.ME2025

Distilling heterogeneous treatment effects: Stable subgroup estimation in causal inference

Melody Huang, Tiffany M. Tang, Ana M. Kenney

Recent methodological developments have introduced new black-box approaches to better estimate heterogeneous treatment effects; however, these methods fall short of providing inter…

stat.ME2024

Towards Generalizing Inferences from Trials to Target Populations

Melody Y Huang, Harsh Parikh

Randomized Controlled Trials (RCTs) are pivotal in generating internally valid estimates with minimal assumptions, serving as a cornerstone for researchers dedicated to advancing c…