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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.
T. D. Breaux, M. W. Vail, and A. I. Antón, “Towards regulatory compliance: Extracting rights and obligations to align requirements with regulations,” in
2006
Earlier work this paper cites.
T. Breaux and A. Antón, “Analyzing regulatory rules for privacy and security requirements,”
2008
Earlier work this paper cites.
T. D. Breaux and D. G. Gordon, “Preserving traceability and encoding meaning in legal requirements extraction,” in
2013
Earlier work this paper cites.
N. Zeni, N. Kiyavitskaya, L. Mich, J. R. Cordy, and J. Mylopoulos, “GaiusT: supporting the extraction of rights and obligations for regulatory compliance,”
2015
Earlier work this paper cites.
N. Zeni, E. A. Seid, P. Engiel, S. Ingolfo, and J. Mylopoulos, “Building large models of law with NómosT,” in
2016
Earlier work this paper cites.
N. Sannier, M. Adedjouma, M. Sabetzadeh, and L. Briand, “An automated framework for detection and resolution of cross references in legal texts,”
2017
Earlier work this paper cites.
J. Bhatia and T. D. Breaux, “Semantic incompleteness in privacy policy goals,” in
2018
Earlier work this paper cites.
A. Sleimi, N. Sannier, M. Sabetzadeh, L. Briand, and J. Dann, “Automated extraction of semantic legal metadata using natural language processing,” in
2018
Earlier work this paper cites.
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “BERT: Pre-training of deep bidirectional transformers for language understanding,” in
2019
Earlier work this paper cites.
Y. Bouzembrak, M. Klüche, A. Gavai, and H. J. Marvin, “Internet of Things in food safety: Literature review and a bibliometric analysis,”
2019
Earlier work this paper cites.
M. Fan, L. Yu, S. Chen, H. Zhou, X. Luo, S. Li, Y. Liu, J. Liu, and T. Liu, “An empirical evaluation of GDPR compliance violations in Android mHealth apps,” in
2020
Earlier work this paper cites.
T. Hey, J. Keim, A. Koziolek, and W. F. Tichy, “NoRBERT: Transfer learning for requirements classification,” in
2020
Earlier work this paper cites.
A. Sainani, P. R. Anish, V. Joshi, and S. Ghaisas, “Extracting and classifying requirements from software engineering contracts,” in
2020
Earlier work this paper cites.
Y. Wang, L. Shi, M. Li, Q. Wang, and Y. Yang, “A deep context-wise method for coreference detection in natural language requirements,” in
2020
Earlier work this paper cites.
O. Amaral, S. Abualhaija, D. Torre, M. Sabetzadeh, and L. C. Briand, “AI-enabled automation for completeness checking of privacy policies,”
2021
Cited alongside, same era.
O. Amaral, S. Abualhaija, M. Sabetzadeh, and L. Briand, “A Model-based conceptualization of requirements for compliance checking of data processing against GDPR,” in
2021
Cited alongside, same era.
R. E. Hamdani, M. Mustapha, D. R. Amariles, A. Troussel, S. Meeùs, and K. Krasnashchok, “A combined rule-based and machine learning approach for automated GDPR compliance checking,” in
2021
Cited alongside, same era.
R. Chatterjee, A. Ahmed, P. R. Anish, B. Suman, P. Lawhatre, and S. Ghaisas, “A pipeline for automating labeling to prediction in classification of NFRs,” in
2021
Cited alongside, same era.
M. K. Habib, S. Wagner, and D. Graziotin, “Detecting requirements smells with deep learning: Experiences, challenges and future work,” in
C. M. Luders, T. Pietz, and W. Maalej, “Automated detection of typed links in issue trackers,” in
2022
Later among the works it cites.
Ş. Mehder and F. B. Aydemir, “Classification of issue discussions in open source projects using deep language models,” in
2022
Later among the works it cites.
D. Torre, S. Abualhaija, M. Sabetzadeh, L. Briand, K. Baetens, P. Goes, and S. Forastier, “An AI-assisted approach for checking the completeness of privacy policies against GDPR,” in
2022
Later among the works it cites.
O. Amaral, S. Abualhaija, and L. Briand, “ML-based compliance verification of data processing agreements against GDPR,” in
2023
Later among the works it cites.
O. Amaral, M. I. Azeem, S. Abualhaija, and L. C. Briand, “NLP-based automated compliance checking of data processing agreements against GDPR,”
2023
Later among the works it cites.
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2021
Cited alongside, same era.
V. Varenov and A. Gabdrahmanov, “Security requirements classification into groups using NLP transformers,” in
2021
Cited alongside, same era.
R. R. Mekala, A. Irfan, E. C. Groen, A. Porter, and M. Lindvall, “Classifying user requirements from online feedback in small dataset environments using deep learning,” in
2021
Cited alongside, same era.
G. Deshpande, B. Sheikhi, S. Chakka, D. L. Zotegouon, M. N. Masahati, and G. Ruhe, “Is BERT the new silver bullet? An empirical investigation of requirements dependency classification,” in
2021
Cited alongside, same era.
J. Fischbach, J. Frattini, A. Spaans, M. Kummeth, A. Vogelsang, D. Mendez, and M. Unterkalmsteiner, “Automatic detection of causality in requirement artifacts: The CiRa approach,” in
2021
Cited alongside, same era.
F. Xie, Y. Zhang, C. Yan, S. Li, L. Bu, K. Chen, Z. Huang, and G. Bai, “Scrutinizing privacy policy compliance of virtual personal assistant apps,” in
2022
Cited alongside, same era.
S. Abualhaija, C. Arora, A. Sleimi, and L. C. Briand, “Automated question answering for improved understanding of compliance requirements: A multi-document study,” in
2022
Cited alongside, same era.
W. Alhoshan, L. Zhao, A. Ferrari, and K. J. Letsholo, “A zero-shot learning approach to classifying requirements: A preliminary study,” in
2022
Cited alongside, same era.
2023
Later among the works it cites.
A. Xiang, W. Pei, and C. Yue, “PolicyChecker: Analyzing the GDPR completeness of mobile apps’ privacy policies,” in
2023
Later among the works it cites.
C. Jain, P. R. Anish, A. Singh, and S. Ghaisas, “A transformer-based approach for abstractive summarization of requirements from obligations in software engineering contracts,” in
2023
Later among the works it cites.
M. Abbas, A. Ferrari, A. Shatnawi, E. Enoiu, M. Saadatmand, and D. Sundmark, “On the relationship between similar requirements and similar software,”
2023
Later among the works it cites.
D. Luitel, S. Hassani, and M. Sabetzadeh, “Using language models for enhancing the completeness of natural-language requirements,” in
2023
Later among the works it cites.
B. Görner and F. B. Aydemir, “Generating requirements elicitation interview scripts with large language models,” in
2023
Later among the works it cites.
Huggingface, “Mixtral,” 2023,
2023
Later among the works it cites.