School of Engineering Department of Computer Science and Engineering 110 Large Language Models as Your Machine Learning Experts Supervisor: DI Shimin / CSE Student: CHAN Chun Man / DA Course: UROP 1100, Summer In recent years, the convergence of Automated Machine Learning (AutoML) and Large Language Models (LLMs) has emerged as a transformative approach in the field of artificial intelligence. This report explores the promising integration of LLMs as pivotal components within AutoML frameworks. Overview of cuttingedge research, including findings from the OptFormer is provided, which illustrates how LLMs can automate complex machine learning processes, thereby reducing the need for extensive human intervention and expertise. Furthermore, established AutoML tools such as auto-sklearn are analyzed, emphasizing their capabilities and the integration of LLM-based methodologies. The findings suggest that leveraging LLMs within AutoML not only enhances automation but also fosters innovation, ultimately contributing to the broader adoption of intelligent systems across diverse industries. Large Language Models as Your Machine Learning Experts Supervisor: DI Shimin / CSE Student: LI Haowei / COMP Course: UROP 1100, Summer This report presents a comprehensive overview of my UROP1100 research experience. The propose of this project is to explore and leverage the power of Large Language Models (LLMs), which aims to integrate with AutoML techniques to perform a more efficient way to automate Machine Learning on Graphs. The first section is a brief overview of the pipeline of our project, ie. AutoGNN with LLMs. The second section is about the work that I’ve done on literature reading to enhance the knowledge of the project especially in the direction of leveraging LLMs in the field of AutoML. The third section is discussion part.
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