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Investigating Strategies for Clause Recommendation

arXiv 2301.10716 ↗First posted 21 Jan 2023cs.CL cs.AIcited by 0

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Abstract (arXiv)

Clause recommendation is the problem of recommending a clause to a legal contract, given the context of the contract in question and the clause type to which the clause should belong. With not much prior work being done toward the generation of legal contracts, this problem was proposed as a first step toward the bigger problem of contract generation. As an open-ended text generation problem, the distinguishing characteristics of this problem lie in the nature of legal language as a sublanguage and the considerable similarity of textual content within the clauses of a specific type. This similarity aspect in legal clauses drives us to investigate the importance of similar contracts' representation for recommending clauses. In our work, we experiment with generating clauses for 15 commonly occurring clause types in contracts expanding upon the previous work on this problem and analyzing clause recommendations in varying settings using information derived from similar contracts.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 9 of its 16 references that are in the map. First posted on arXiv 21 Jan 2023.

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References · 9

  1. 2017Attention Is All You Needcited by 59,932
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  3. 2017Billion-scale similarity search with GPUscited by 2,477
  4. 2016Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphscited by 853
  5. 2021CUAD: An Expert-Annotated NLP Dataset for Legal Contract Reviewcited by 232
  6. 2020LEGAL-BERT: The Muppets straight out of Law Schoolcited by 111
  7. 2018CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Servicecited by 72
  8. 2020A Benchmark for Lease Contract Reviewcited by 26
  9. 2021CLAUSEREC: A Clause Recommendation Framework for AI-aided Contract Authoringcited by 4

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