mlsanityData to 7 Oct 2026

CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review

arXiv 2103.06268 ↗First posted 10 Mar 2021cs.CL cs.LGcited by 232

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Cited by 22 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Many specialized domains remain untouched by deep learning, as large labeled datasets require expensive expert annotators. We address this bottleneck within the legal domain by introducing the Contract Understanding Atticus Dataset (CUAD), a new dataset for legal contract review. CUAD was created with dozens of legal experts from The Atticus Project and consists of over 13,000 annotations. The task is to highlight salient portions of a contract that are important for a human to review. We find that Transformer models have nascent performance, but that this performance is strongly influenced by model design and training dataset size. Despite these promising results, there is still substantial room for improvement. As one of the only large, specialized NLP benchmarks annotated by experts, CUAD can serve as a challenging research benchmark for the broader NLP community.

Key facts. Cited by 232 papers in the map (data through 7 Oct 2026). Builds on 19 of its 29 references that are in the map. First posted on arXiv 10 Mar 2021.

Builds on

19 of 29 references.

References · 19

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 7; 2022: 22; 2023: 32; 2024: 40; 2025: 49; 2026: 82.

232 papers.

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  1. 2023A Survey on Evaluation of Large Language Modelscited by 1,227
  2. 2024Jamba: A Hybrid Transformer-Mamba Language Modelcited by 390
  3. 2023LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Modelscited by 328
  4. 2021LexGLUE: A Benchmark Dataset for Legal Language Understanding in Englishcited by 302
  5. 2023L-Eval: Instituting Standardized Evaluation for Long Context Language Modelscited by 232
  6. 2022Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Modelscited by 187
  7. 2021ContractNLI: A Dataset for Document-level Natural Language Inference for Contractscited by 145
  8. 2021DEMix Layers: Disentangling Domains for Modular Language Modelingcited by 130
  9. 2024A Survey on Large Language Model Acceleration based on KV Cache Managementcited by 125
  10. 2021Lawformer: A Pre-trained Language Model for Chinese Legal Long Documentscited by 115
  11. 2024RAGBench: Explainable Benchmark for Retrieval-Augmented Generation Systemscited by 115
  12. 2022Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Datasetcited by 113
38 more
  1. 2024LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domaincited by 113
  2. 2021MultiEURLEX -- A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfercited by 89
  3. 2022Position: Considerations for Differentially Private Learning with Large-Scale Public Pretrainingcited by 86
  4. 2023Large Language Models and Knowledge Graphs: Opportunities and Challengescited by 71
  5. 2022Legal Prompt Engineering for Multilingual Legal Judgement Predictioncited by 54
  6. 2024DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processingcited by 49
  7. 2022Multi-LexSum: Real-World Summaries of Civil Rights Lawsuits at Multiple Granularitiescited by 47
  8. 2023Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Modelscited by 46
  9. 2022A Multi-Task Benchmark for Korean Legal Language Understanding and Judgement Predictioncited by 44
  10. 2025MMDocIR: Benchmarking Multimodal Retrieval for Long Documentscited by 43
  11. 2024Natural Language Processing for the Legal Domain: A Survey of Tasks, Datasets, Models, and Challengescited by 42
  12. 2021A Statutory Article Retrieval Dataset in Frenchcited by 40
  13. 2022LEVEN: A Large-Scale Chinese Legal Event Detection Datasetcited by 36
  14. 2025CARROT: A Cost Aware Rate Optimal Routercited by 34
  15. 2022The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applicationscited by 32
  16. 2023MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understandingcited by 32
  17. 2023Unlocking Practical Applications in Legal Domain: Evaluation of GPT for Zero-Shot Semantic Annotation of Legal Textscited by 32
  18. 2025Characterizing Deep Research: A Benchmark and Formal Definitioncited by 29
  19. 2024Is It Really Long Context if All You Need Is Retrieval? Towards Genuinely Difficult Long Context NLPcited by 27
  20. 2024OCR Hinders RAG: Evaluating the Cascading Impact of OCR on Retrieval-Augmented Generationcited by 24
  21. 2025Position: Don't Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapointscited by 22
  22. 2022How to Steer Your Adversary: Targeted and Efficient Model Stealing Defenses with Gradient Redirectioncited by 21
  23. 2023A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontierscited by 21
  24. 2025MM-R5: MultiModal Reasoning-Enhanced ReRanker via Reinforcement Learning for Document Retrievalcited by 21
  25. 2024Evaluating the Performance of Large Language Models via Debatescited by 19
  26. 2024Chain of Logic: Rule-Based Reasoning with Large Language Modelscited by 18
  27. 2022LegalBench: Prototyping a Collaborative Benchmark for Legal Reasoningcited by 17
  28. 2022ClassActionPrediction: A Challenging Benchmark for Legal Judgment Prediction of Class Action Cases in the UScited by 17
  29. 2023GENTLE: A Genre-Diverse Multilayer Challenge Set for English NLP and Linguistic Evaluationcited by 17
  30. 2023The Cambridge Law Corpus: A Dataset for Legal AI Researchcited by 14
  31. 2025Enabling Self-Improving Agents to Learn at Test Time With Human-In-The-Loop Guidancecited by 14
  32. 2022BudgetLongformer: Can we Cheaply Pretrain a SotA Legal Language Model From Scratch?cited by 13
  33. 2023Can ChatGPT Perform Reasoning Using the IRAC Method in Analyzing Legal Scenarios Like a Lawyer?cited by 12
  34. 2023PrivImage: Differentially Private Synthetic Image Generation using Diffusion Models with Semantic-Aware Pretrainingcited by 12
  35. 2025Towards Reliable Retrieval in RAG Systems for Large Legal Datasetscited by 12
  36. 2023Distill or Annotate? Cost-Efficient Fine-Tuning of Compact Modelscited by 11
  37. 2024ChronosLex: Time-aware Incremental Training for Temporal Generalization of Legal Classification Taskscited by 11
  38. 2025ACORD: An Expert-Annotated Retrieval Dataset for Legal Contract Draftingcited by 11

50 most cited of 232 All 232 (JSON)