10 papers
Admission Without Answers: Label-Free Certification and Experience Learning for LLM-Based Optimization Modeling
Junbo Jacob Lian, Huiling Chen, Hanzhang Qin +1
Agents that learn from experience improve at optimization modeling by storing solved trajectories and reusing them as skills. A wrong trajectory that enters the library can be retr…
Which Model Is Actually Serving You? IRIS: Budgeted Black-Box Auditing of Model Substitution and Routing Dilution in LLM Gateways
Yuewei Zhang, Zhi-Hai Zhang, Hanzhang Qin
Commercial LLM gateways mediate access to hosted models, but the served backend may not match the advertised one: it may substitute a cheaper model on every request or route only a…
Best-Arm Identification with Generative Proxy
Tianyi Ma, Hanzhang Qin, Ruihao Zhu +1
Best-arm identification is a canonical model for data-driven decision-making, but in many applications each reward observation is costly. Motivated by the growing availability of c…
Huge-Scale Assortment Optimization with Customer Choice: A Parallel Primal-Dual Approach
Donghao Zhu, Hanzhang Qin, Ching-pei Lee +3
We study huge-scale assortment optimization problems to maximize expected revenue under customer choice, addressing a fundamental challenge in industries such as transportation, re…
ReLoop: Structured Modeling and Behavioral Verification for Reliable LLM-Based Optimization
Junbo Jacob Lian, Yujun Sun, Huiling Chen +3
Large language models (LLMs) can translate natural-language problem descriptions into optimization code, but the code is prone to silent failures: it executes and returns a solver-…
Large-Scale Optimization Model Auto-Formulation: Harnessing LLM Flexibility via Structured Workflow
Kuo Liang, Yuhang Lu, Jianming Mao +7
Large-scale optimization is a key backbone of modern business decision-making. However, building these models is often labor-intensive and time-consuming. We address this by propos…
CogniPair: From LLM Chatbots to Conscious AI Agents -- GNWT-Based Multi-Agent Digital Twins for Social Pairing -- Dating & Hiring Applications
Wanghao Ye, Sihan Chen, Yiting Wang +18
Current large language model (LLM) agents lack authentic human psychological processes necessary for genuine digital twins and social AI applications. To address this limitation, w…
Testing Fairness with Utility Tradeoffs: A Wasserstein Projection Approach
Yan Chen, Zheng Tan, Jose Blanchet +1
Ensuring fairness in data driven decision making has become a central concern across domains such as marketing, lending, and healthcare, but fairness constraints often come at the…
Thompson Sampling for Repeated Newsvendor
Li Chen, Hanzhang Qin, Yunbei Xu +2
In this paper, we investigate the performance of Thompson Sampling (TS) for online learning with censored feedback, focusing primarily on the classic repeated newsvendor model--a f…
On Pareto Optimality for Parametric Choice Bandits
Jierui Zuo, Hanzhang Qin
We study online assortment optimization under stochastic choice when a decision maker simultaneously values cumulative revenue performance and the quality of post-hoc inference on…