Argument Generation

Argument generation, the automated creation of persuasive texts, aims to improve the logical soundness and coherence of outputs from large language models (LLMs). Current research focuses on enhancing LLMs' ability to avoid logical fallacies, generate diverse perspectives through multi-agent frameworks and persona-based approaches, and control argument structure using techniques like Rhetorical Structure Theory. This field is significant because improved argument generation can mitigate the spread of misinformation, enhance human-computer interaction in debate and dialogue systems, and assist in various professional domains such as law and finance.