Evidence-Gated LLM Priors for Multi-Objective Bayesian Optimization

ArXi:2606.01730v1 Announce Type: new Large language models (LLMs) are increasingly used as heuristic advisors for black-box optimization, yet their suggestions and self-reported confidence are not necessarily calibrated to downstream objective values. This issue becomes pronounced in multi-objective Bayesian optimization, where different objectives may require different expert knowledge and where an LLM expert can be useful for one objective but misleading for another.