AI RESEARCH
Adaptive Simulation Experiment for LLM Policy Optimization
arXiv CS.LG
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ArXi:2604.08779v1 Announce Type: new Large language models (LLMs) have significant potential to improve operational efficiency in operations management. Deploying these models requires specifying a policy that governs response quality, shapes user experience, and influences operational value. In this research, we treat LLMs as stochastic simulators and propose a pairwise comparison-based adaptive simulation experiment framework for identifying the optimal policy from a finite set of candidates.