206 citations · 218 across the 23 of their papers we have counts for
38 papers
When Representative Samples Produce Worse Outcomes: Scale-up Decisions and Testing in Small-Budget RCTs
Hannah Li, Hongseok Namkoong, Isaac Scheinfeld
Small randomized controlled trials are often used to screen interventions before running larger follow-up studies. This is a critical phase of experimentation, as missing effective…
Local Sensitivity Under Transport Restrictions
Hongseok Namkoong
We quantify the value of structural knowledge, restrictions a modeler places on the world before seeing data. Our analytic workhorse is the local sensitivity of an estimand to dist…
Empirical Likelihood for Nonsmooth Functionals
Hongseok Namkoong
Empirical likelihood is an attractive inferential framework that respects natural parameter boundaries, but existing approaches typically require smoothness of the functional and m…
LLM Swiss Round: Aggregating Multi-Benchmark Performance via Competitive Swiss-System Dynamics
Jiashuo Liu, Jiayun Wu, Chunjie Wu +5
The rapid proliferation of Large Language Models (LLMs) and diverse specialized benchmarks necessitates a shift from fragmented, task-specific metrics to a holistic, competitive ra…
FinSearchComp: Towards a Realistic, Expert-Level Evaluation of Financial Search and Reasoning
Liang Hu, Jianpeng Jiao, Jiashuo Liu +20
Search has emerged as core infrastructure for LLM-based agents and is widely viewed as critical on the path toward more general intelligence. Finance is a particularly demanding pr…
DRO: A Python Library for Distributionally Robust Optimization in Machine Learning
Jiashuo Liu, Tianyu Wang, Henry Lam +2
We introduce dro, an open-source Python library for distributionally robust optimization (DRO) for regression and classification problems. The library implements 14 DRO formulation…