Statistical Inference in Large Language Models

Large Language Models (LLMs) have recently stood out as revolutionary AI tools for processing data in the form of text. However, when harnessing their potential for statistical decision-making, it becomes essential to understand the risks of their outputs. Evaluating the uncertainty and confidence levels associated with LLMs presents both challenges and intriguing opportunities for today's statisticians. The aim of this one-day short course is to equip statisticians with the skills to integrate inferential concepts into the applications and advancement of LLMs. Course topics include: 1) a brief introduction to the fundamentals of LLMs, tailored for those new to transformers and deep learning; 2) a primer on statistical inference techniques specifically for text data using LLMs; and 3) in-depth exploration of LLM applications in medical domains and the broader data science field. By the end of the course, attendees will possess the skills needed to empower LLMs with statistical inference. While this course promises a deep and enriching dive into the confluence of statistics and advanced AI, no prior knowledge of LLMs is required.