Large Language Models and Control

Large Language Models (LLMs) are reshaping how we think, learn, and innovate — and control theorists have a critical role to play in this transformation. This workshop dives into the powerful intersection of control theory and LLMs, exploring how these generative models can enhance control research, and how control principles can help improve the safety, reliability, and scalability of LLMs themselves.

In this workshop, you will learn how to:

1. Contribute to LLMs with Control Theory: We will introduce the control community to how control-theoretic tools and perspectives can advance the development, safety, and scalability of LLMs — bringing rigor and structure to a fast-moving domain.

2. Apply LLMs in Control Research: We will showcase how LLMs can serve as practical tools for control theorists, aiding tasks such as controller design, motion planning, safety assurance, and autonomous systems.

Whether you're eager to influence the next generation of AI, or looking to harness LLMs in your own research, this session will equip you with the insights and tools to lead at this dynamic frontier. 

Join us as we bridge two rapidly evolving fields and be part of the transformation!