19 papers
Two-Timescale Hierarchical Reinforcement Learning for Resilient Operations
Young Hyun Cho, Franz Stoll, Will Wei Sun +2
Unexpected shocks recur in global operations, requiring decision rules that adapt as market and operating conditions change. Many operational systems also have hierarchical structu…
Low Rank for Rank: Uncertainty-Aware Task-Specific LLM Ranking under Sparse Pairwise Comparisons
Jiachun Li, David Simchi-Levi, Will Wei Sun
Pairwise human-preference platforms such as Chatbot Arena have become central to large language model (LLM) evaluation, yet reliable task-specific ranking remains challenging. Glob…
When Should an AI Workflow Release? Always-Valid Inference for Black-Box Generate-Verify Systems
Young Hyun Cho, Will Wei Sun
LLM-enabled AI workflows increasingly produce outputs through iterative generate-evaluate-revise loops. Each iteration can improve the candidate, but it also creates a release deci…
Policy-Aware Design of Large-Scale Factorial Experiments
Xin Wen, Xi Chen, Will Wei Sun +1
Digital firms routinely run many online experiments on shared user populations. When product decisions are compositional, such as combinations of interface elements, flows, message…
LLM Evaluation as Tensor Completion: Low Rank Structure and Semiparametric Efficiency
Jiachun Li, David Simchi-Levi, Will Wei Sun
Large language model (LLM) evaluation platforms increasingly rely on pairwise human judgments. These data are noisy, sparse, and non-uniform, yet leaderboards are reported with lim…
Reinforcement Learning from Human Feedback: A Statistical Perspective
Pangpang Liu, Chengchun Shi, Will Wei Sun
Reinforcement learning from human feedback (RLHF) has emerged as a central framework for aligning large language models (LLMs) with human preferences. Despite its practical success…