We introduce OpenDebateEvidence, a comprehensive dataset for argument mining
and summarization sourced from the American Competitive Debate community. This
dataset includes over 3.5 million documents with rich metadata, making it one
of the most extensive collections of debate evidence. OpenDebateEvidence
captures the complexity of arguments in high school and college debates,
providing valuable resources for training and evaluation. Our extensive
experiments demonstrate the efficacy of fine-tuning state-of-the-art large
language models for argumentative abstractive summarization across various
methods, models, and datasets. By providing this comprehensive resource, we aim
to advance computational argumentation and support practical applications for
debaters, educators, and researchers. OpenDebateEvidence is publicly available
to support further research and innovation in computational argumentation.
Access it here: this https URL

我们介绍了 OpenDebateEvidence，这是一个从美国竞争辩论社区收集的全面的论点挖掘和总结数据集。该数据集包括超过 350 万个具有丰富元数据的文档，是最大的辩论证据集之一。OpenDebateEvidence 捕捉了高中和大学辩论中论点的复杂性，为训练和评估提供了宝贵的资源。我们的大量实验证明了对最新大型语言模型进行微调以进行论辩抽象总结的有效性，涵盖了各种方法、模型和数据集。通过提供这一全面的资源，我们旨在推动计算论证的发展，并支持辩论者、教育工作者和研究人员的实际应用。OpenDebateEvidence 已公开可用，以支持计算论证的进一步研究和创新。在此访问：this https URL