Issue 1  December 4th 2023

Large Language Models as Optimizers

OPRO also offers several advantages over traditional derivative-based algorithms. Firstly, OPRO allows for optimization in natural language, making it accessible to a broader range of users who may not have a background in mathematical optimization techniques. This opens up the possibility for non-experts to easily leverage the power of optimization in their applications. Secondly, the iterative nature of OPRO allows for continuous improvement and refinement of solutions over multiple optimization steps. This can be especially beneficial for complex problems where finding an optimal solution may require multiple iterations and adjustments. Lastly, using large language models as optimizers provides a scalable and flexible approach that can be applied to various optimization problems across different domains.

Overall, the OPRO framework presents a promising approach to optimization by leveraging the capabilities of large language models. Its ability to generate and refine solutions in natural language and its superior performance compared to human-designed prompts make it a valuable tool for various real-world applications. As further advancements are made in natural language processing and large language models, the potential for OPRO to revolutionize the optimization field is immense.

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