Position Paper: Leveraging Foundational Models for Black-Box Optimization: Benefits, Challenges, and Future Directions

arXiv:2405.03547v1 Announce Type: new
Abstract: Undeniably, Large Language Models (LLMs) have stirred an extraordinary wave of innovation in the machine learning research domain, resulting in substantial impact across diverse fields such as reinforcement learning, robotics, and computer vision. Their incorporation has been rapid and transformative, marking a significant paradigm shift in the field of machine learning research.
However, the field of experimental design, grounded on black-box optimization, has been much less affected by such a paradigm shift, even though integrating …

abstract arxiv benefits box challenges computer computer vision cs.ai cs.lg cs.ne diverse domain fields foundational foundational models future impact innovation language language models large language large language models llms machine machine learning optimization paper reinforcement reinforcement learning research robotics type vision