Target Argument

Target argument research focuses on computationally modeling and analyzing arguments, aiming to improve automated reasoning and decision-making systems. Current research emphasizes developing sophisticated models, including those based on graph convolutional networks, large language models, and logic programming, to handle complex argument structures, uncertainty, and diverse perspectives. This work has implications for various fields, such as improving online debate moderation, enhancing AI explainability, and developing more robust and ethical AI systems by providing methods for evaluating and generating arguments. The development of large-scale datasets and shared tasks is also driving progress in this area.