# High Quality Real-Time Structured Debate Generation

arXiv: https://arxiv.org/abs/2012.00209 · HTML: https://mlsanity.com/paper/2012.00209/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Dec 2020.

## Built on by (most cited first, 2 of 2)

- [Argue with Me Tersely: Towards Sentence-Level Counter-Argument Generation](https://mlsanity.com/paper/2312.13608/) (2023)
- [Overview of AI-Debater 2023: The Challenges of Argument Generation Tasks](https://mlsanity.com/paper/2407.14829/) (2024)

## Abstract (arXiv)

Automatically generating debates is a challenging task that requires an understanding of arguments and how to negate or support them. In this work we define debate trees and paths for generating debates while enforcing a high level structure and grammar. We leverage a large corpus of tree-structured debates that have metadata associated with each argument. We develop a framework for generating plausible debates which is agnostic to the sentence embedding model. Our results demonstrate the ability to generate debates in real-time on complex topics at a quality that is close to humans, as evaluated by the style, content, and strategy metrics used for judging competitive human debates. In the spirit of reproducible research we make our data, models, and code publicly available.