Evaluating LLMs for Text Summarization: An Introduction

Large language models (LLMs) have shown tremendous potential across various applications. However, deploying LLMs without human supervision and evaluation could lead to significant errors including, in the worst case, the potential loss of life. In this blog post from the Carnegie Mellon University Software Engineering Institute (SEI), we outline the fundamentals of LLM evaluation for text summarization in high-stakes applications such as intelligence report summarization. We first discuss the challenges of LLM evaluation, give an overview of the current state of the art, and finally detail how we are filling the identified gaps at the SEI.