论文标题
高质量的实时结构化辩论生成
High Quality Real-Time Structured Debate Generation
论文作者
论文摘要
自动产生辩论是一项具有挑战性的任务，需要了解论点以及如何否定或支持它们。在这项工作中，我们定义了辩论树木和途径，以产生辩论，同时实施高级结构和语法。我们利用与每个参数相关的元数据的大量树木结构辩论。我们开发了一个框架来生成合理的辩论，这对句子嵌入模型不可知。我们的结果表明，通过用于判断竞争性人类辩论的样式，内容和策略指标评估，具有接近人类的复杂主题的实时辩论的能力。本着可重复的研究精神，我们公开提供数据，模型和代码。
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.
