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1 Ergebnisse
1
Prompting Creative Requirements via Traceable and Adversari..:
, In:
2023 IEEE 31st International Requirements Engineering Conference (RE)
,
Gudaparthi, Hemanth
;
Niu, Nan
;
Wang, Boyang
... - p. 134-145 , 2023
Link:
https://doi.org/10.1109/RE57278.2023.00022
RT T1 <cTitle>2023 IEEE 31st International Requirements Engineering Conference (RE)</cTitle>: T1 <Title>Prompting Creative Requirements via Traceable and Adversarial Examples in Deep Learning</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10260978&Exemplar=1&LAN=DE A1 Gudaparthi, Hemanth A1 Niu, Nan A1 Wang, Boyang A1 Bhowmik, Tanmay A1 Liu, Hui A1 Zhang, Jianzhang A1 Savolainen, Juha A1 Horton, Glen A1 Crowe, Sean A1 Scherz, Thomas A1 Haitz, Lisa YR 2023 SN 2332-6441 K1 Deep learning K1 Perturbation methods K1 Instruments K1 Computer architecture K1 Software K1 Behavioral sciences K1 Requirements engineering K1 creative requirements K1 automated requirements generation K1 deep learning K1 adversarial examples SP 134 OP 145 LK http://dx.doi.org/https://doi.org/10.1109/RE57278.2023.00022 DO https://doi.org/10.1109/RE57278.2023.00022 SF ELIB - SuUB Bremen
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