3 papers
cs.AI2026
Automated Design of Inventory Policy with Large Language Models: An Exploratory Study
Fenghua Yang, Preet Baxi, Yi Zhang +4
Firms making inventory decisions have access to operational data, optimization tools, and large language models (LLMs). Typically, data characterize the operating environment, opti…
cs.DS2026
Sequential Sampling for Binary Classification: Two LLMs are (Almost) All You Need
Guokai Li, Alys Liang, Mo Liu +4
We study how to orchestrate multiple large language models (LLMs) for reliable binary classification when models differ in accuracy, monetary cost, and response time. A decision-ma…
stat.ME2026
Minimizing Type 2 Errors in an Experiment-Rich Regime via Optimal Resource Allocation
Fenghua Yang, Dae Woong Ham, Stefanus Jasin
Randomized experiments (often known as "A/B tests") are widely used to evaluate product and service innovations. We study how to allocate limited experimentation resources across M…