Automated Contract-Related Summarization Task

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An Automated Contract-Related Summarization Task is a automated topic-focused summarization task that is a contract summarization task.



References

2024

  • Ken Adams. (2024). “Something Else to Not Use AI For: Summarizing Contracts."
    • NOTES:
      • The article updates a previous post to provide a detailed critique of using AI for summarizing contracts, emphasizing the unchanged conclusion despite added detail.
      • The article explores the inherent dysfunction in mainstream contract language and how AI, trained on such language, replicates these issues in an unpredictable manner.
      • The article evaluates AI summarization through an example, comparing summaries from different versions of ChatGPT and highlighting inaccuracies and omissions.
      • The article argues against the usefulness of summarizing contracts, stating that every element of a contract is critical and that summarization often leads to significant omissions or alterations.
      • The article suggests that outlining contracts is a preferable alternative to summarization, offering a structured approach that highlights key elements without oversimplification.
      • The article critiques AI's ability to effectively summarize or outline contracts, pointing out the limitations of AI in capturing the nuanced details necessary for accurate legal interpretation.
      • The article includes specific criticisms of AI summarization, such as the omission of important references, the generalization of defined terms, and the simplification of legal standards.
      • The article emphasizes the importance of direct engagement with the actual contract text to understand its implications fully, cautioning against reliance on AI for legal analysis.
      • The article contributes to the broader discussion on the limitations of AI in complex, nuanced tasks like legal document interpretation, advocating for cautious integration of AI into legal practices.

2023

2022

  1. https://www.tldrlegal.com
  2. We will publicly release this dataset.

2019

  1. (Over et al., 2007) ⇒ Paul Over, Hoa Dang, and Donna Harman (2007). “DUC in Context". In: Information Processing & Management, 43(6):1506–1520.
  2. (Mihalcea & Tarau, 2004) ⇒ Rada Mihalcea, and Paul Tarau (2004). “Textrank: Bringing Order into Text". In: Proceedings of the 2004 conference on empirical methods in natural language processing.
  3. (Haghighi & Vanderwende, 2009) ⇒ Aria Haghighi, and Lucy Vanderwende (2009). “Exploring content models for multi-document summarization. In: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pages 362–370.