OptiHive: Ensemble Selection for LLM-Based Optimization via Statistical Modeling
OptiHive introduces a two-stage framework to improve solvers generated from natural language descriptions of optimization problems. It first filters components using an Integer Linear Program to keep only interpretable parts, then uses a latent-class model to statistically estimate the true performance of remaining solvers and tests. This allows for principled uncertainty quantification and higher quality solvers.