Decision Process Automation with Large Language Models

Large Language Models impress with their adeptness in context-aware text generation, logic, as well as reasoning. Typically, downstream models fine tuned on chat data possess the remarkable ability to be directed towards solving tasks described in natural language without explicit further weight adaptation. In relevant applications, interesting use cases often relate multiple external data sources with each other and are characterized by a complex multistep decision process. In this talk, we discuss how predefining decision steps and integrating external data filtering can break down multifaceted problems into manageable, self-contained language processing tasks, which can readily be solved by LLMs.