mlsanityData to 7 Oct 2026

Plain English Summarization of Contracts

arXiv 1906.00424 ↗First posted 2 Jun 2019cs.CLcited by 28

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Abstract (arXiv)

Unilateral contracts, such as terms of service, play a substantial role in modern digital life. However, few users read these documents before accepting the terms within, as they are too long and the language too complicated. We propose the task of summarizing such legal documents in plain English, which would enable users to have a better understanding of the terms they are accepting. We propose an initial dataset of legal text snippets paired with summaries written in plain English. We verify the quality of these summaries manually and show that they involve heavy abstraction, compression, and simplification. Initial experiments show that unsupervised extractive summarization methods do not perform well on this task due to the level of abstraction and style differences. We conclude with a call for resource and technique development for simplification and style transfer for legal language.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Jun 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 3; 2023: 4; 2024: 7; 2025: 6; 2026: 3.

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  1. 2021A Statutory Article Retrieval Dataset in Frenchcited by 40
  2. 2022EUR-Lex-Sum: A Multi- and Cross-lingual Dataset for Long-form Summarization in the Legal Domaincited by 39
  3. 2024I Don't Know: Explicit Modeling of Uncertainty with an [IDK] Tokencited by 26
  4. 2022Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluationcited by 23
  5. 2024Leveraging Large Language Models for Learning Complex Legal Concepts through Storytellingcited by 23
  6. 2023Investigating Hallucinations in Pruned Large Language Models for Abstractive Summarizationcited by 16
  7. 2021Robust Deep Reinforcement Learning for Extractive Legal Summarizationcited by 10
  8. 2024LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domaincited by 10
  9. 2023The Law and NLP: Bridging Disciplinary Disconnectscited by 8
  10. 2022Agent-Specific Deontic Modality Detection in Legal Languagecited by 7
  11. 2025A Comprehensive Survey on Legal Summarization: Challenges and Future Directionscited by 6
  12. 2025Evaluating the Evaluators: Are readability metrics good measures of readability?cited by 6
16 more
  1. 2025The Massive Legal Embedding Benchmark (MLEB)cited by 6
  2. 2021Privacy Policy Question Answering Assistant: A Query-Guided Extractive Summarization Approachcited by 5
  3. 2024Optimizing Numerical Estimation and Operational Efficiency in the Legal Domain through Large Language Modelscited by 5
  4. 2024Enterprise Benchmarks for Large Language Model Evaluationcited by 5
  5. 2025VLQA: The First Comprehensive, Large, and High-Quality Vietnamese Dataset for Legal Question Answeringcited by 4
  6. 2021Fairness-aware Summarization for Justified Decision-Makingcited by 3
  7. 2024Legal Fact Prediction: The Missing Piece in Legal Judgment Predictioncited by 3
  8. 2023Data and Approaches for German Text simplification -- towards an Accessibility-enhanced Communicationcited by 2
  9. 2024How Private are Language Models in Abstractive Summarization?cited by 2
  10. 2021VieSum: How Robust Are Transformer-based Models on Vietnamese Summarization?cited by 1
  11. 2023Analyzing Hong Kong's Legal Judgments from a Computational Linguistics point-of-viewcited by 1
  12. 2025The Medium Is Not the Message: Deconfounding Document Embeddings via Linear Concept Erasurecited by 1
  13. 2026Evaluation of Large Language Models in Legal Applications: Challenges, Methods, and Future Directionscited by 1
  14. 2025CourtPressGER: A German Court Decision to Press Release Summarization Datasetcited by 0
  15. 2026HAKARI-Bench: A Lightweight Benchmark for Comparing Retrieval Architectures and Efficiency Settings under Unified Conditionscited by 0
  16. 2026CorporateBench: Large-Scale Q&A Benchmarking with Temporal Knowledge Basescited by 0