Control Logic

Control logic research focuses on developing methods to reliably and flexibly control the behavior of complex systems, particularly large language models (LLMs) and other AI agents. Current efforts leverage techniques like Hidden Markov Models and deterministic finite automata to impose logical constraints on LLM outputs, improving adherence to user instructions and enabling verifiable sequential decision-making. This work is significant for enhancing the reliability and trustworthiness of AI systems across diverse applications, from text generation and interactive editing to robotic control and industrial automation.