mlsanityData to 7 Oct 2026

OpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset

arXiv 2406.14657 ↗First posted 20 Jun 2024cs.CL cs.AI cs.LGcited by 8

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Abstract (arXiv)

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/Hellisotherpeople/OpenDebateEvidence-Anonymized

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 14 of its 24 references that are in the map. First posted on arXiv 20 Jun 2024.

Builds on

14 of 24 references.

References · 14

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  2. 2018Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarizationcited by 1,308
  3. 2021QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarizationcited by 363
  4. 2019BillSum: A Corpus for Automatic Summarization of US Legislationcited by 117
  5. 2020From Arguments to Key Points: Towards Automatic Argument Summarizationcited by 60
  6. 2019Corpus Wide Argument Mining -- a Working Solutioncited by 36
  7. 2020DebateSum: A large-scale argument mining and summarization datasetcited by 34
  8. 2019Are You Convinced? Choosing the More Convincing Evidence with a Siamese Networkcited by 29
  9. 2022ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Miningcited by 25
  10. 2022IAM: A Comprehensive and Large-Scale Dataset for Integrated Argument Mining Taskscited by 23
  11. 2021Extracting Fine-Grained Knowledge Graphs of Scientific Claims: Dataset and Transformer-Based Resultscited by 10
  12. 2023LMGQS: A Large-scale Dataset for Query-focused Summarizationcited by 9
2 more
  1. 2020QBSUM: a Large-Scale Query-Based Document Summarization Dataset from Real-world Applicationscited by 8
  2. 2023VivesDebate-Speech: A Corpus of Spoken Argumentation to Leverage Audio Features for Argument Miningcited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 4.

8 papers.

  1. 2025Large Language Models in Argument Mining: A Surveycited by 14
  2. 2025OpenReview Should be Protected and Leveraged as a Community Asset for Research in the Era of Large Language Modelscited by 5
  3. 2025MODS: Moderating a Mixture of Document Speakers to Summarize Debatable Queries in Document Collectionscited by 4
  4. 2025ArgCMV: An Argument Summarization Benchmark for the LLM-eracited by 3
  5. 2026PERSPECTRA: A Scalable and Configurable Pluralist Benchmark of Perspectives from Argumentscited by 3
  6. 2026ArgBench: Benchmarking LLMs on Computational Argumentation Taskscited by 1
  7. 2026Evaluating LLM-Driven Summarisation of Parliamentary Debates with Computational Argumentationcited by 1
  8. 2026A dataset of rated conceptual argumentscited by 1