Text Evaluation

Text evaluation, the process of assessing the quality of generated text, aims to develop objective and reliable methods for measuring various aspects of text quality, such as fluency, coherence, and factual accuracy. Current research heavily utilizes large language models (LLMs) as both evaluators and tools for improving existing metrics, focusing on areas like multi-agent evaluation frameworks, the development of human-aligned metrics that reduce reliance on extensive human annotation, and the exploration of LLM internal representations for improved evaluation. These advancements are crucial for improving the reliability and efficiency of text generation systems across diverse applications, ranging from automated writing assistance to scientific idea assessment and educational tools.