Abstract Large Language Models to Enhance Bayesian Optimization (LLAMBO) LLAMBO, by Liu et al., is a novel approach that integrates Large Language Models (LLMs) into the Bayesian Optimization (BO) framework to improve the optimization of complex, expensive-to-evaluate black-box functions. By leveraging the contextual understanding and few-shot learning capabilities of LLMs, LLAMBO enhances multiple facets of the BO pipeline:
Zero-Shot Warmstarting
LLAMBO frames the optimization problem in natural language, allowing the LLM to propose promising initial solutions.