Text Distribution

Text distribution analysis focuses on understanding and manipulating the statistical properties of text data, aiming to improve various natural language processing tasks. Current research emphasizes developing methods to balance skewed distributions in training data for large language models (LLMs), detect AI-generated text by analyzing its divergence from human-written text, and describe differences between text distributions using natural language summaries. These advancements have significant implications for improving LLM performance, mitigating biases and ethical concerns in AI-generated content, and facilitating more nuanced analyses of textual data across diverse applications.