mlsanityData to 7 Oct 2026

ACORD: An Expert-Annotated Retrieval Dataset for Legal Contract Drafting

arXiv 2501.06582 ↗First posted 11 Jan 2025cs.CLcited by 11

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Abstract (arXiv)

Information retrieval, specifically contract clause retrieval, is foundational to contract drafting because lawyers rarely draft contracts from scratch; instead, they locate and revise the most relevant precedent. We introduce the Atticus Clause Retrieval Dataset (ACORD), the first retrieval benchmark for contract drafting fully annotated by experts. ACORD focuses on complex contract clauses such as Limitation of Liability, Indemnification, Change of Control, and Most Favored Nation. It includes 114 queries and over 126,000 query-clause pairs, each ranked on a scale from 1 to 5 stars. The task is to find the most relevant precedent clauses to a query. The bi-encoder retriever paired with pointwise LLMs re-rankers shows promising results. However, substantial improvements are still needed to effectively manage the complex legal work typically undertaken by lawyers. As the first retrieval benchmark for contract drafting annotated by experts, ACORD can serve as a valuable IR benchmark for the NLP community.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 18 of its 39 references that are in the map. First posted on arXiv 11 Jan 2025.

Builds on

18 of 39 references.

References · 18

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6 more
  1. 2021Lepard: Learning partial point cloud matching in rigid and deformable scenescited by 85
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  5. 2024CLERC: A Dataset for Legal Case Retrieval and Retrieval-Augmented Analysis Generationcited by 18
  6. 2021CLAUSEREC: A Clause Recommendation Framework for AI-aided Contract Authoringcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 8; 2026: 3.

11 papers.