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pro vyhledávání: '"Hassani, Shabnam"'
Autor:
Hassani, Shabnam
This research explores the application of Large Language Models (LLMs) for automating the extraction of requirement-related legal content in the food safety domain and checking legal compliance of regulatory artifacts. With Industry 4.0 revolutionizi
Externí odkaz:
http://arxiv.org/abs/2404.17522
As software-intensive systems face growing pressure to comply with laws and regulations, providing automated support for compliance analysis has become paramount. Despite advances in the Requirements Engineering (RE) community on legal compliance ana
Externí odkaz:
http://arxiv.org/abs/2404.14356
Natural language (NL) is arguably the most prevalent medium for expressing systems and software requirements. Detecting incompleteness in NL requirements is a major challenge. One approach to identify incompleteness is to compare requirements with ex
Externí odkaz:
http://arxiv.org/abs/2308.03784
[Context and motivation] Incompleteness in natural-language requirements is a challenging problem. [Question/problem] A common technique for detecting incompleteness in requirements is checking the requirements against external sources. With the emer
Externí odkaz:
http://arxiv.org/abs/2302.04792
Akademický článek
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This repository contains the implementation and evaluation artifacts for the REFSQ 2023 paper titled "Using Language Models for Enhancing the Completeness of Natural-language Requirements", authored by Dipeeka Luitel, Shabnam Hassani and Mehrdad Sabe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::648c5a42e726ef76a9cc011684b67ac9