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: https://huggingface.co/datasets/Yusuf5/OpenCaselist

翻译：我们介绍了OpenDebateEvidence，这是一个源自美国竞技辩论社群的、用于论据挖掘与摘要的综合性数据集。该数据集包含超过350万份文档及丰富的元数据，使其成为最广泛的辩论证据集合之一。OpenDebateEvidence捕捉了高中及大学辩论中论点的复杂性，为训练与评估提供了宝贵资源。我们的大量实验证明了，在各种方法、模型和数据集上，对最先进的大型语言模型进行微调以用于论证性抽象摘要的有效性。通过提供这一综合性资源，我们旨在推进计算论证领域的发展，并为辩手、教育工作者和研究人员提供实际应用支持。OpenDebateEvidence已公开可用，以支持计算论证领域的进一步研究与创新。访问地址：https://huggingface.co/datasets/Yusuf5/OpenCaselist