A Robustness Evaluation Framework for Argument Mining

little is usually known about the model’s stability and consistency when deployed in real-world settings. In this paper, we propose a robustness evaluation framework to guide the design of rigorous argument mining models. As part of the framework, we introduce several novel robustness tests tailored specifically to argument mining tasks. Additionally, we integrate existing robustness tests designed for other natural language processing tasks and re-purpose them for argument mining.