Exploring the Use of Large Language Models for Reference-Free Text Quality Evaluation: An Empirical Study

Understand

Evaluating the quality of generated text is a challenging task in NLP, due to the inherent complexity and diversity of text.

• Recently, large language models (LLMs) have garnered significant attention due to their impressive performance in various tasks.
• Therefore, we present this paper to investigate the effectiveness of LLMs, especially ChatGPT, and explore ways to optimize their use in assessing text quality.
• We compared three kinds of reference-free evaluation methods.