Investigating Strategies for Clause Recommendation
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Making Language Model a Hierarchical Classifier and Generator
Mitigating Object Hallucinations via Sentence-Level Early Intervention
The Devil behind the mask: An emergent safety vulnerability of Diffusion LLMs
Hashed Watermark as a Filter: Defeating Forging and Overwriting Attacks in Weight-based Neural Network Watermarking
Seq vs Seq: An Open Suite of Paired Encoders and Decoders
OpenFActScore: Open-Source Atomic Evaluation of Factuality in Text Generation
토론
이 논문과 연결된 포럼 글이 아직 없습니다.