Rhetorical Structure Theory

Rhetorical Structure Theory (RST) is a framework for analyzing the hierarchical organization of discourse, aiming to understand how sentences and clauses relate to form coherent texts. Current research focuses on applying RST to improve natural language processing tasks like summarization, machine translation, and argument mining, often leveraging graph neural networks and large language models to parse and generate text with improved structure and coherence. These advancements are driving progress in various NLP applications by enabling more nuanced understanding and generation of complex textual structures, ultimately leading to more sophisticated and human-like AI systems.