From Human-in-the-Loop to LLM-in-the-Loop Bayesian Optimization

This work introduces a collaborative Bayesian optimization approach that re-integrates human input into the data-driven decision-making process. By combining high-throughput Bayesian optimization with discrete decision theory, experts can influence the selection of experiments via a discrete choice.